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   Abstract
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Year : 2004  |  Volume : 7  |  Issue : 25  |  Page : 49-57
Children's cognition and aircraft noise exposure at home-the West London Schools Study

Department of Psychiatry, Queen Mary, University of London, UK

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  Abstract 

The association of aircraft noise exposure with cognitive performance was examined by means of a cross-sectional field survey. Two hundred thirty six children attending 10 primary schools around Heathrow Airport in west London were tested on reading comprehension, immediate/delayed recall and sustained attention. In order to obtain the information about their background, a questionnaire was delivered to the parents and 163 answers were collected. Logistic regression models were used to assess performance on the cognitive tests in relation to aircraft noise exposure at home and possible individual and school level confounding factors. A significant dose-response relationship was found between aircraft noise exposure at home and performance on memory tests of immediate/delayed recall. However there was no strong association with the other cognitive outcomes. These results suggest that aircraft noise exposure at home may affect children's memory.

Keywords: Aircraft noise, cross-sectional survey, children, cognition, memory

How to cite this article:
Matsui T, Stansfeld S, Haines M, Head J. Children's cognition and aircraft noise exposure at home-the West London Schools Study. Noise Health 2004;7:49-57

How to cite this URL:
Matsui T, Stansfeld S, Haines M, Head J. Children's cognition and aircraft noise exposure at home-the West London Schools Study. Noise Health [serial online] 2004 [cited 2019 Oct 17];7:49-57. Available from: http://www.noiseandhealth.org/text.asp?2004/7/25/49/31647

  Introduction Top


A number of studies have shown that aircraft noise exposure impairs cognitive performance in school children (Cohen et al. 1980, Evans et al. 1995; Hygge et al. 2002; Hiramatsu et al. 2003). In these studies noise exposure has effects on complex cognitive tasks such as reading and, in some studies, long term memory.

In many of these studies noise exposure has been selected on the basis of the school which they attend (Cohen et al. 1980; Haines et al. 2001a, b, c; Hiramatsu et al. 2003). The supposition behind this choice of sample selection is that most of children's learning occurs at school and thus noise exposure at school is most pertinent to its influence on cognitive performance. However, children are only at school for about six and a half hours each day and much of children's education takes place informally outside school hours. Thus it seems reasonable to ask what effects noise exposure at home might have on children's cognitive performance. Children attending primary school often live quite close to their schools and thus their aircraft noise exposure at school and at home may be similar. If there is sufficient variation in home noise exposure it is possible to examine how this affects cognitive performance.

This paper presents results from the West London Schools Study examining the association of aircraft noise exposure at home on cognitive performance taking into account aircraft noise exposure at school. It was anticipated that noise exposure at home would have an additional effect in terms of impairment of cognitive performance to that found for aircraft noise exposure at school.


  Method Top


Design

In this cross-sectional epidemiological field study, children in the fourth grade attending 20 co-education state primary schools around Heathrow Airport in West London were tested on cognitive performance (for complete details on the methods of the West London Schools Study see Haines et al., 2001c). Ten schools were located in high-aircraft noise-impact urban areas (16-hr outdoor LAeq >63dB) and the other 10 schools were in low-aircraft noise-impact urban areas (16-hr outdoor LAeq <57dB). The children were already randomly selected into mixed ability classes. The cognitive performance tests were group-administered in the classrooms. Parents of the children were given a questionnaire enquiring about the children's health and sociodemographic background, which might affect the cognitive performance. The relation between the cognitive performance and aircraft noise exposure at home was analysed statistically.

Noise exposure and participants

The data on aircraft noise exposure level at each participating child's home were taken from the published 1997 Civil Aviation Authority dBA Leq,16hr (92 days) contour maps indicating the average continuous equivalent sound level of outdoor aircraft noise within a particular area for 16 hours during the daytime (Leq,16hr can be converted into Ldn or Leq,24h by subtracting approximately 2dB). The noise level at home varied from under 57dB to over 66dB among children attending the 10 high noise schools. However, 96% of the children of the 10 low noise schools lived in low noise homes (see the results section for details). In this paper, therefore, we excluded the sample from the low noise schools. As a result, the participants were 236 fourth grade children (age 8-9, 117 boys and 119 girls) attending the 10 schools in the highly noise exposed areas.

Cognitive Performance Outcome Measures Reading Comprehension: This was measured using the Suffolk Reading Scale (Hagley, 1987) Level 2, which contains 70 multi-choice questions with 4 potential answers. The Suffolk Reading Scale was designed to measure the reading ability and reading standards of 6 year 4 month to 13 year 11 month students in the United Kingdom. The Suffolk Reading Scale has been standardized on a large randomly selected and representative, ethnically and socio-≠economically mixed, national sample of primary aged school children.

Long Term Memory recall and recognition: Long term memory was measured by a task similar to the task in the Munich Study (Evans et al. 1995, Hygge et al. 2002). The task used was adapted for group administration from the Child Memory Scale (Cohen, 1997). The task was designed to measure the immediate and delayed recall and recognition of two stories. In the immediate portion, two stories are played on an audiocassette. The subjects are asked to write down as much as they can remember on a sheet. In the delayed portion, after a 30 minutes delay and interference task (Suffolk Reading Scale), the subjects are asked again to write down as much as they can remember of the stories. After the delayed recall task, the recognition task was assessed by 30 factual questions with yes or no responses. The answers were scored by using a standardized procedure for the Children's Memory Scale (Cohen, 1997), and 3 scores (immediate recall, delayed recall and recognition scores) were calculated.

Sustained attention: This was measured with the Score task taken from Tests of Everyday Attention for Children (TEA-Ch) battery of measures for the assessment of attention in children (version A, Manly et al. 1998). In this task, the children are asked to imagine that they are keeping score by counting the scoring sounds in a computer game. This test measures ability to count tones with irregular inter-stimulus intervals. There are 10 trials each scored for correct number of items counted.

Measurement of confounding factors: The household deprivation score was calculated on a scale adapted from Townsend's Scale (Townsend et al. 1989) by incorporating: income, home tenure, car ownership, employment status, central heating, social class and household crowding in a single scale (these data were collected from parents). A total deprivation score was calculated from the number of indicators of household deprivation reported out of these 7 indices. Missing values on employment status were imputed with the child's eligibility for free school meal status and missing values on income and social class of unemployed parents were imputed as low and manual categories respectively. Mother's educational level was also asked in the questionnaire. The information on main language spoken at home was collected from the children, parents and school.


  Statistical Procedures Top


Multiple logistic regression analyses were applied to examine the relationship between home noise level and cognitive outcomes. For the logistic regression, the cognitive outcome scores were converted into dichotomous variables by using medians of the distributions as cut off points to define high and low scoring groups. Dichotomization may lose some information of the scale variables. However, results obtained by logistic regression analyses are more reliable than those obtained by ANCOVA which is based on many assumptions e.g. normality, linearity and homogeneity. The advantage of parametric tests is limited to the case where the assumptions are met in the data (Siegel and Castellan, 2000). In this study, we did not have enough information on the validity of the assumption of ANCOVA.

The effects of noise level were adjusted for age, sex, main language spoken at home, deprivation, mother's educational level and individual schools. The nominal variable of school was included to adjust for noise level at school and educational and social differences between the schools. Trend analyses were also carried out to examine the dose-response relationship between home noise level and cognitive outcomes assuming linear dose-response relationship between noise level and log-odds. Goodness of fit of the logistic regression model to the data was verified by Hosmer-Lemeshow test and a check on the residuals. All statistical tests were two-tailed with P=0.05 (calculation with SPSS version 10.0).


  Results Top


Descriptive results

The number of children who participated in the cognitive tests was 236 in the high noise schools and 215 in the low noise schools. The rate of the participation was 83% in the high noise schools and 81% in the low noise schools. 163 and 154 parent answers were entered into the analysis from high and low noise schools respectively.

[Table - 1] shows the number of valid responses on Suffolk reading scale stratified by noise level at home and school. There is a variation of noise level at home in the high noise schools. However, almost all the subjects in low noise schools live in low noise areas exposed to less than 57dB. Therefore, the subjects of low noise schools were excluded in the following analyses.

Outdoor noise exposure level is used as a noise measure in this study. The noise level inside might be affected by noise insulation of the houses. In the high noise schools, however, 91% of children's houses had double glazing windows and there was no relation between the proportion of double-glazed houses and noise level at home.

Simple statistics for the cognitive outcome measures in the high noise schools are shown in [Table - 2]. The median values were used as cut-off points to convert these outcome measures into dichotomous variables for the logistic regression model.

Effect of noise on cognitive performance

The results of a trend test will show the significance of dose-response relationships assuming a linear trend of odds ratios among three groups classified by noise level at home. [Table - 3] shows odds ratios of five cognitive outcomes against noise level at home. On reading comprehension, the number of correct answers to 15 difficult questions (Haines et al. 2001c) was also analysed.

Significant trends of dose-response relationship with noise level were detected on immediate recall (P=0.006) and delayed recall (P=0.002) after adjustment for age, sex, deprivation score, language spoken at home, mother's education level and school. Odds ratios in the highest noise group (>66dB) were 4.71 on immediate and 5.45 on delayed recall, and significant odds ratio was also obtained in the moderate noise group on delayed recall (P=0.030, OR=3.22) compared to the reference group defined as low noise(< 63 dB) within the high noise exposed sample. On the other three outcomes (reading mean score, reading on difficult questions and sustained attention), the trend tests did not show significant dose-response relationships, however, all the odds ratios on the other three outcomes were greater than 1 in the highest noise groups.

The detailed results of logistic regression analysis on immediate and delayed recall adjusting for potential confounding factors are shown in [Table - 4] and [Table - 5]. The odds ratio in the highest noise group on immediate/delayed recall was greater than or nearly equal to the odds ratios of deprivation score and mother's education level. The odds ratios of schools varied widely from 0.768 to 2.640 on immediate recall, from 1.000 to 8.029 on delayed recall (school A was unintentionally selected as a reference category).


  Discussion Top


In summary, an association was found between aircraft noise exposure level at home and impairment of immediate and delayed recall of memory, which remained as a dose-response relationship, even after adjustment for noise exposure level at school. Noise levels at home did not show either consistent or strong effects on reading comprehension or sustained attention.

The effect of aircraft noise exposure on delayed recall is in keeping with the similar findings from the Munich Study (Evans et al. 1995, Hygge et al. 2002) and the Okinawa Study (Hiramatsu et al. 2003). However, these results should be interpreted cautiously as a similar effect was not demonstrated in relation to school noise exposure in this study (Haines et al. 2001c). It was unexpected that a similar effect was found for immediate and delayed recall. Immediate recall was included as a control outcome in the study, with stronger noise effects expected for delayed recall which involves a more complex memory component. This might suggest an artifactual explanation for these findings. Nevertheless, there are three points that do not support an artifactual explanation. First, a highly significant dose response association was shown between memory impairment and home noise exposure level. Secondly, the results remained even after adjustment for potential confounding factors including school educational quality and mother's education level. Thirdly, the obtained odds ratios in the highest noise group were higher than those of almost all the confounding factors. The delayed recall was measured 30 minutes after the immediate recall test. The time interval, however, may have been insufficient to find the differences between immediate and delayed recall. Moreover, it is possible that the delayed recall performance may be influenced by what was reported by subjects at immediate recall, as well as, what was remembered at encoding the text.

It is difficult to understand why we found an effect of chronic aircraft noise at school on difficult items in the Suffolk Reading Comprehension but no effect on either immediate or delayed recall (Haines et al. 2001c) whereas aircraft noise exposure at home was related to immediate or delayed recall but not to reading comprehension. Of course, the comparison by school noise exposure included low noise exposed schools while the home noise exposure analyses did not. This might amount for the lack of effect of home noise exposure on reading comprehension. With enough sample size, significant results could be found also on reading comprehension. Could it also be the case that chronic exposure to aircraft noise at home affects cognitive function differently from aircraft noise exposure at school? This seems unlikely but clearly future studies need to take more account of noise exposure both at home and at school. If children learn basic cognitive skills such as memory at home, the role of the home environment seems to be important for interpretation of these results.

Among the five outcomes, immediate/delayed recall was tested using an open question. On the other hand, reading comprehension and delayed recognition were tested with multiple-choice tests. Generally, an open question is more difficult than a multiple-choice question and it is related to motivation to answer. Negative effect of noise on long term memory was found especially in difficult questions (Hygge 1993), which may support the present results of immediate/delayed recall tests. Moreover, chronic exposure to aircraft noise was associated with decreased motivation in school children (Cohen et al. 1980; Evans 1993, Evans et al. 1995). The deficit of immediate/delayed recall test could be caused by the decreased motivation influenced by aircraft noise exposure. Since the motivation of school children is also influenced by daily education and suggestion by their teachers, the score of recall might be confounded by the school education. The obtained results, however, were fully adjusted for the difference between schools that may be a proxy indicator of educational quality. Therefore, we can arrive at the conclusion that aircraft noise affects the score of children's recall test, to be more precise, it affects children's long term memory and this may be partly due to motivation.


  Conclusion Top


A cross sectional survey of children's cognitive performance and aircraft noise was conducted around Heathrow airport. Five outcomes of reading comprehension, sustained attention, and immediate/delayed recall were obtained from 236 students in 10 high noise schools, and 163 valid answers to the questionnaire were collected from their parents. The results suggest that there is a dose-response relationship between noise level at home and the ratio of students having lower score on delayed and immediate recall after adjustment for age, sex, spoken language at home, deprivation, mother's education level and school. The results suggest that aircraft noise causes disadvantage to children's memory. However, further studies are necessarily to confirm the effect on memory.


  Acknowledgement Top


We would like to thank the children, parents and teachers who took part in study. Without their generous participation this research would not have been possible. We would like to acknowledge our collaboration with Sarah Brentnall (Queen Mary), Mark Jiggins and Bernard Berry at the National Physical Laboratory. We would like to acknowledge tremendous assistance provided by Rhiannon Roberts in collecting these data. This research was conducted working in partnership with the local education and environmental authorities and health agencies around Heathrow Airport. We thank them for supporting our project. The West London Schools Study, undertaken by Queen Mary, University of London was jointly funded by Department of Health and Department of the Environment and Transport and the Regions. The views expressed in this publication are those of the authors and not necessarily those of the Department of Health and Departments of the Environment and Transport and the Regions.[14]

 
  References Top

1.Cohen, S., Evans, G.W., Krantz, D.S., & Stokols, D. (1980). Physiological, motivational and cognitive effects of aircraft noise on children: Moving from the laboratory to the field. American Psychologist, 35, 231-243.  Back to cited text no. 1    
2.Cohen, M.J. (1997). Children's Memory Scale Manual. San Antonio: The Psychological Corporation Harcourt Brace and Company.  Back to cited text no. 2    
3.Evans, G.W. (1993). Nonauditory Effects of Noise on Children: A Critical Review. Children's Environments, 10(1), 31-51.  Back to cited text no. 3    
4.Evans, G.W., Hygge, S. & Bullinger, M. (1995). Chronic noise and psychological stress. Psychological Science, 6, 333-338.  Back to cited text no. 4    
5.Hagley, F. (1987). Suffolk Reading Scale. Windsor: NFER-NELSON.  Back to cited text no. 5    
6.Haines, M.M., Stansfeld, S.A., Job, R.F.S., Berglund, B. & Head, J. (2001a). Chronic aircraft noise exposure, stress responses mental health and cognitive performance in school children. Psychological Medicine, 31, 265-277.  Back to cited text no. 6    
7.Haines, M.M., Stansfeld, S.A., Job, R.F.S, Berglund, B. & Head, J. (2001b). A follow-up study of the effects of chronic aircraft noise exposure on child stress responses and cognition. International Journal of Epidemiology, 30, 839-845.  Back to cited text no. 7    
8.Haines, M.M., Stansfeld, S.A., Brentnall, S., Head, J., Berry, B., Jiggins, M., & Hygge, S. (2001c). West London Schools Study: the effect of chronic aircraft noise exposure on child health. Psychological Medicine, 31, 1385-1396.  Back to cited text no. 8    
9.Hiramatsu, K., Tokuyama, T., Matsui, T., Miyakita, T., Osada, Y. & Yamamoto, T. (2003). The Okinawa study: effect of chronic aircraft noise exposure on memory of school children. Proc. 8th International conference on Noise as a Public Health Problem, 179-180.  Back to cited text no. 9    
10.Hygge, S. (1993). A comparison between the impact of noise from aircraft, road traffic and trains on long term recall and recognition of text in children aged 12-14 years. Schriftenr Ver Wasser Boden Lufthyg, 88, 416-427.  Back to cited text no. 10    
11.Hygge, S., Evans, G.W., Bullinger M. (2002). A prospective study of some effects of aircraft noise on cognitive performance in schoolchildren. Psychological Science, 13, 469-474.  Back to cited text no. 11    
12.Manly, T., Robertson, I.H., Anderson, V., & Nimmo≠Smith, I. (1998) Tests of Everyday Attention for Children. Thames Valley Test Company, Flempton.  Back to cited text no. 12    
13.Siegel, S. & Castellan, N.J. (2000) Nonparametric statistics for the behavioral sciences, McGraw-hill, New York.  Back to cited text no. 13    
14.Townsend, P., Phillimore, P., & Beattie, A. (1989). Health and Deprivation. London: Routledge.  Back to cited text no. 14    

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Correspondence Address:
T Matsui
Department of Urban and Environmental Engineering, Graduate School of Engineering, Kyoto University, Sakyo, Kyoto 606-8501, Japan

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Source of Support: None, Conflict of Interest: None


PMID: 15703149

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    Tables

  [Table - 1], [Table - 2], [Table - 3], [Table - 4], [Table - 5]

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