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  Table of Contents    
Year : 2013  |  Volume : 15  |  Issue : 64  |  Page : 165-172
The association between road traffic noise exposure and blood pressure among children in Germany: The GINIplus and LISAplus studies

1 Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg; Faculty of Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany
2 Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg, Germany; School of Population and Public Health, The University of British Columbia, Canada
3 Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg; Division of Metabolic Diseases and Nutritional Medicine, Ludwig-Maximilians-University of Munich, Dr. von Hauner Children's Hospital, Munich, Germany
4 Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg, Germany
5 Department of Environmental Hygiene, Federal Environment Agency, Berlin, Germany
6 Department of Paediatrics, Technical University of Munich, Munich, Germany
7 Ludwig-Maximilians-University of Munich, Dr. von Hauner Children's Hospital, Division of Paediatric Gastroenterology and Hepatology, Munich, Germany

Click here for correspondence address and email
Date of Web Publication21-May-2013

Studies examining the association between road traffic noise and blood pressure in children are scarce. Nighttime noise levels and window orientations have not been considered in most previous studies. Investigate the association between road traffic noise exposure and blood pressure among children, and investigate the impact of bedroom window direction on this association. We measured blood pressure in 605 children aged 10 years from two Munich cohorts. Demographic and health information was collected by parent completed questionnaires. Road traffic noise levels were assessed by day-evening-night noise indicator "Lden" and night noise indicator "Lnight". Minimum and maximum levels within a 50 m buffer around child's home address were derived. Generalized additive models were applied to explore effect of noise levels on systolic and diastolic blood pressure (SBP and DBP). The orientation of child's bedroom window was considered in sensitivity analyses. DBP was significantly associated with the minimum level of noise during 24 h (Lden_min) and nightime (Lnight_min). Specifically, DBP increased by 0.67 and 0.89 mmHg for every 5 A-weighted decibels increase in Lden_min and Lnight_min. After adjusting for Lden_min (Lnight_min), DBP of children whose bedroom window faced the street was 1.37 (1.28) mmHg higher than those whose bedroom window did not, these children showed statistically significant increased SBP for Lden_min (3.05 mmHg) and Lnight_min (3.27 mmHg) compared to children whose bedroom window did not face the street. Higher minimum levels of weighted day-evening-night noise and nighttime noise around the home residence may increase a child's blood pressure.

Keywords: Blood pressure, children, nighttime, road traffic noise, windows

How to cite this article:
Liu C, Fuertes E, Tiesler CM, Birk M, Babisch W, Bauer CP, Koletzko S, Heinrich J. The association between road traffic noise exposure and blood pressure among children in Germany: The GINIplus and LISAplus studies. Noise Health 2013;15:165-72

How to cite this URL:
Liu C, Fuertes E, Tiesler CM, Birk M, Babisch W, Bauer CP, Koletzko S, Heinrich J. The association between road traffic noise exposure and blood pressure among children in Germany: The GINIplus and LISAplus studies. Noise Health [serial online] 2013 [cited 2023 Mar 22];15:165-72. Available from: https://www.noiseandhealth.org/text.asp?2013/15/64/165/112364

  Introduction Top

Transportation is the main source of environmental noise pollution. [1] Approximately 54% of European Union (EU) citizens that live in major agglomerations (>500,000 inhabitants) are exposed to road traffic noise with a weighted day-evening-night equivalent sound pressure level of 55 A-weighted decibels [dB(A)] or more, whereas 15% are exposed to levels above 65 dB(A). Along densely traveled roads, levels can exceed 75 dB(A). During nighttime, more than 18% of EU citizens are exposed to night noise levels of 55 dB(A) or more. [2] Long-term exposure to noise may cause adverse effects on health such as annoyance, disturbance of sleep or daily activities, hearing disorders, hypertension and ischemic heart disease. [3]

Most previous epidemiological studies conclude that noise exposure may cause adverse health effects. However, studies on children are limited, especially with respect to road-traffic-related noise as most previous studies have focused on aircraft noise. [4] To date, there have been seven reliable epidemiological studies on road-traffic noise and blood pressure in children. However, no unequivocal conclusions can be drawn from these results; Two of the seven studies found positive and significant associations between noise exposure and diastolic blood pressure (DBP), [5],[6] one study found negative and significant associations between noise and DBP, [7] four studies found positive and significant associations between noise and systolic blood pressure (SBP), [6],[7],[8],[9] one study found a positive but non-significant association between noise and SBP [10] and one study found a negative and significant associations for SBP. [3]

The effect of nighttime noise exposure on health has been seldom explored in children. [3] Belojevic et al. [7] reported a positive correlation between SBP and noise during the day, but not at night. Paunovic et al. [6] found the same result in their study, as well as a similar correlation between DBP and noise (again, only the day noise was correlated positively). Furthermore, the direction of child's bedroom is rarely considered among studies on noise and health. [11]

According to Sorensen et al., [12] exposure to noise during the night may cause sleep disturbance, potentially resulting in a stress reaction which activates the sympathetic and endocrine system ultimately leading to changes in blood pressure. As explained by van Kempen et al., [13] we are exposed to noise during sleep, which may cause the fluctuation of blood pressure in the body. As also suggested in the paper, although the change in blood pressure caused by noise exposure may be small, this increase, which could affect the prevalence of cardiovascular disease, may still have an important impact as a large percent of the population is exposed.

The aim of the present study is to investigate the association between modeled road traffic noise exposure (noise levels for both 24 h and nighttime) and blood pressure among children aged 10 years, and to investigate the impact of the direction of the bedroom window on this association.

  Methods Top

Study population

The study population consists of participants from two German birth cohorts of healthy full-term neonates (gestational age ≥ 37 weeks).

The German Infant Nutritional Intervention plus (GINIplus) environmental and genetic influences on allergy development study was initiated to prospectively investigate the influence of a nutrition intervention during infancy, as well as the effects of air pollution and genetics on allergy development. Details of the design, recruitment and follow-up of this intervention study have been previously published. [14],[15] In brief, a total of 5991 newborns were recruited in obstetric clinics in Munich and Wesel, Germany, between September 1995 and July 1998. Follow-up occurred at the age of 1-4, 6 and 10 years of age. Fifty-five percent of those originally recruited at birth could be followed until the age of 10 years.

The lifestyle-related factors on the immune system and the development of allergies in childhood plus the influence of traffic emissions and genetics (LISAplus) population-based study was designed to assess the influence of lifestyle-related factors on the immune system, air pollution, and genetics on the development of allergies in childhood. In total, 3095 healthy full-term neonates were recruited from 14 obstetrical clinics in Munich, Leipzig, Wesel and Bad Honnef between November 1997 and January 1999 (original recruitment was 3097 children, but two withdrew their consent to participate). Follow-up for this cohort occurred at the age of 6, 12 and 18 months, and 2, 4, 6 and 10 years. Fifty-seven percent of the original population could be followed until the age of 10 years. A detailed description of screening and recruitment is described elsewhere. [16],[17]

We restricted our present analysis to the Munich area for which a road traffic noise map was available. To be included, a child must have reported their home address to be within Munich at birth and at the 10 year follow-up (GINIplus N = 709, LISAplus N = 444, total N = 1153). Of these children, 52% participated in a clinical physical examination in the 10 th year of follow-up during which blood pressure measurements were taken (GINIplus 405, LISAplus 200 in total N = 605). [Figure 1] shows the overall design of the study population.
Figure 1: Design of study population

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For both cohort studies, ethical approval was obtained by the medical ethical committees of all participating institutes and the medical association of the state of Bavaria (Landesaerztekammer). Written informed consent was obtained from all active participating families.

Outcome definition and covariates

At the 10-year follow-up, blood pressure, height, weight, and age (in months) were collected during a physical examination. Resting blood pressure measurements, including SBP and DBP, were carried out twice following standardized guidelines: Blood pressure was measured on the right arm, except in the case of injuries or other obstacles (e.g., gypsum) when it was measured on the left arm. The measurement was performed with the child in a sitting position after 5 min rest. The elbow was relaxed, at heart level, and slightly bent, and the upper arm was bare during testing. A second measurement was taken after sitting for a further 2 min. An automatic blood pressure monitor (Omron M5 Professional) was used for the blood pressure measurements. The cuff size was selected according to the length and circumference of the upper arm of each child: the width was at least 2/3 the length and the pressure bladder covered at least half of the circumference of the upper arm. All the blood pressure measurements were conducted between 7:00 a.m. and 8:30 p.m. by the same physician. The average of the two measurements was used throughout this analysis, regardless of the difference between the two records (we excluded 11 subjects who had only one measurement).

Demographic, health, and lifestyle information on the subjects was collected using self-administered questionnaires completed by the parents [gender, physical activity (hours per week), maternal smoking during pregnancy (yes/no), parental history of hypertension (neither parent is hypertensive; at least, one of the parents is hypertensive), and the highest educational level of parents (low: Both parents with less than 10 years of school; medium: 10 years of school; high: One of the parents with more than 10 years of school)].

Geographic information system modeled road traffic noise exposure

A GIS based noise model, including the entire Munich street network (around 2800 km) was used to estimate road traffic noise levels for the year 2007 on a 5 m grid, 4 m above ground level, in 5 dB(A)-intervals. Details of the modeling approach have been published previously. [18] Briefly, weighted equivalent noise levels in dB(A) over a full day (Lden, weighted yearly average noise level between 6 a.m. to 6 p.m., 6 p.m. to 10 p.m., and 10 p.m. to 6 a.m.) and at night (Lnight, yearly average noise level between 10 p.m. and 6 a.m., as German regulations stipulate) were modeled according to the European Noise Directive. [19]

Maximum and minimum levels of noise within a 50 m buffer around each child's home address were used in this study. Maximum noise over a full day (Lden_max) was defined as the maximum noise level of Lden within a 50 m buffer around the selected building/house. Minimum noise over a full day (Lden_min), maximum noise at nighttime (Lnight_max) and minimum noise at nighttime (Lnight_min) were defined analogously.

Statistical analysis

The descriptive analysis was carried out using the statistical software package SPSS 17.0. Pearson's Chi-square, the Student's t-test, and Wilcoxon rank sum test were used to assess differences of baselines characters between GINIplus and LISAplus; one-way ANOVA was used to analysis distribution of blood pressure between different levels of noise, which were divided into three categories based on quartiles with cutoffs at the 25 th and 75 th percentile.

Given that the correlation between noise and blood pressure was nearly linear, we explored the effect of road-traffic noise (as a linear term) on blood pressure using generalized additive models (GAM), other confounders [age of child, body mass index (BMI) of child at the age of 10 and physical activity], which were not found to be in a linear relationship with blood pressure were analyzed using splines.

Three models were used to test associations. The first model included adjustments for cohort (GINIplus; LISAplus), gender, age of child, BMI at the age of 10, time of physical examination (divided into four groups January to April, May to July, August to September and October to December), physical activity, maternal smoking during pregnancy, parental history of hypertension, and parental educational level (Model 1; included participants for both cohorts combined). The second model included the same covariates as Model 1, but was restricted to the LISAplus participants (Model 2). The third model (Model 3) was the same as model 2, but also included an adjustment for the direction of the child's bedroom window (facing street, not facing street). As window direction was only available for the LISAplus participants, Model 2 was necessary to accurately assess the impact of incorporating the direction of the bedroom window (comparing Models 2 and 3). All risk estimates were modeled per 5 dB(A) increase in noise exposure. All results are presented as coefficients with corresponding 95% confidence intervals (95% CI). P values below 0.05 were used to indicate conventional statistical significance. All models were constructed using the MGCV package in the R statistical software.

  Results Top

Among the 1153 subjects with available noise measurements, 605 of them participated in the 10-year physical examination and provided two blood pressure measurements (GINIplus 405, LISAplus 200; [Figure 1]).

Basic characteristics of the participants, stratified by cohort and pooled are shown in [Table 1]. In general, Lnight_max is approximately 10 dB(A) lower than Lden_max [spearman correlation coefficient is 0.965 (P value < 0.001); for Lden_min and Lnight_min, the spearman correlation coefficient is 0.915 (P value < 0.001)]. GINIplus study have significantly higher BMI and SBP compared to LISAplus participants.
Table 1: Baseline characteristics of the study participants

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The distribution of blood pressure levels across noise exposure categories is presented in [Table 2]. DBP appears to increase across increasing Lden_max, Lden_min and Lnight_min noise categories, the latter of which is statistically significant (P value = 0.019). In addition, SBP increases across increasing Lnight_min categories, and the association is not significant.
Table 2: Distribution of blood pressure across levels of noise exposure

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Associations between road traffic noise exposure and blood pressure are presented in [Table 3]. No significant associations between maximum noise exposure and blood pressure were observed. For minimum noise exposure, DBP was significantly associated with Lden_min and Lnight_min after confounder adjustment [0.67 (0.11, 1.24) mmHg and 0.89 (0.20, 1.58) mmHg increase per 5 dB(A), respectively]. The associations between DBP and Lden_min and Lnight_min remained significant after adjusting for the direction of the bedroom window [Model 3, β = 1.14 (0.21, 2.07); β = 1.73 (0.57, 2.88), respectively].
Table 3: The association between traffic noise exposure and blood pressure

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SBP was not associated with any measure of noise exposure (Models 1 and 2). However, after taking the direction of the child's bedroom window into account, a statistically significant association was observed between SBP and Lnight_min [Model 3, β = 1.62 (0.16, 3.09)].

[Table 3] also shows that, after adjusting for Lden_min and other variables, the SBP of children whose bedroom window faced the street was 3.05 (0.10, 6.00) mmHg higher compared to children whose bedroom window did not. For Lnight_min, the SBP of children whose bedroom window faced the street was 3.27 (0.34, 6.20) mmHg higher compared to those whose bedroom window did not.

With respect to the covariates, parental hypertension had a significant effect on SBP [mean β = 3.20, all P value = 0.001 across the four different noise factors] and DBP [mean β = 1.82, range of P values (0.024, 0.030) across the four different noise factors]. The gender of the child also had a significant effect on DBP [mean β = 1.80, range of P values (0.008, 0.009) across the four different noise factors].

  Discussion Top

We investigated associations between road traffic noise and blood pressure among 605 children aged 10 years. DBP was associated with Lden_min and Lnight_min after adjusting for relevant covariates, and the associations remained significant after considering the direction of the bedroom window. No significant associations between SBP and noise exposures were found in the basic models, but a significant association between SBP and Lnight_min was observed after adjusting for the direction of the window in the child's bedroom. We also found that, after adjusting for noise levels and other covariates, children whose window faced a street had a significantly higher SBP compared to those whose bedroom did not.

Although negative associations between noise and blood pressure have been previously reported, the positive association between DBP and noise in our study is in agreement with most past studies. For example, Belojevic et al. reported a 3 mmHg significant difference in DBP between children from noisy schools and residences (57.18 mmHg) compared to those living in more quiet environments (60.18 mmHg). [20] Conversely, in a study of 1542 children aged 3-7 years in the Slovak Republic, association between 24-h equivalent urban traffic noise around kindergartens/residences and blood pressure was explored, the DBP of children living in noisy homes was 2 mmHg higher than those living in quiet homes. [5] In addition, Paunovic et al. explored the effect of road traffic noise on blood pressure among 856 children aged 7-11 years, using noise levels at schools during the day and at the home address during the night as the exposure. This study found a positive and significant association between DBP and noise levels at schools, mean levels of blood pressures for children at noisy and quiet schools were 60.0 mmHg and 58.2 mmHg, respectively. [20] Babisch et al. [9] also reported similar results in their study, in which 1048 children aged 8-14 were investigated and noise levels in front of child's (bed-) room between 8:00 and 23:30 were recorded. In this study, a 1.0 mmHg difference in DBP between children from residences located at busy-traffic (65.9 mmHg) and low-traffic (64.8 mmHg) streets was found. This study also reported a significant increase in DBP (0.61 mmHg, 95% CI: 0.08-1.15 mmHg) per 10 dB(A) increase in average noise level around the child's (bed-) room.

In our study, noise was more strongly associated with DBP than with SBP. One explanation may be that noise exposure increases peripheral vascular tone, which has been observed by Andren et al. [21] and Neus et al. [22] under experimental laboratory conditions. Another explanation may be a reduction of "dipping" due to noise exposure, such as was reported by Haralabidis et al. [23] In their study, the authors suggested that blood pressure during sleep show a physiological decline with reference to daytime values ("dipping"), the extent of which is associated with noise (a 0.8% less dipping in DPB per 5 dB(A) increase in measured road traffic noise was reported). [23] These studies support the relationship between both Lden_min and Lnight_min and DBP observed in our work.

This study has several important limitations. First, there is a potential for selection bias, as only 12.7% (1153 out of 9086) of the original GINIplus and LISAplus populations could be included in this study due to the availability of the noise exposure levels (only available for the city of Munich). In addition, only 52.47% (605 out of 1153) of the selected subjects underwent blood pressure measurements 10 years later. However, there were no significant differences between noise levels of children who provided blood pressure information and those who did not. Nevertheless, we found that children who underwent blood pressure measurements were more physically active (P < 0.01) and their parents were less likely to have hypertension (P < 0.01) or have a high level of education (P = 0.037). Second, we do not have information on the hearing levels (abilities) of the children. Children with and without hearing deficiencies could be differently affected by similar noise levels. Third, as mentioned by van Kempen et al., [13] a common problem of this and most past study is that not all relevant noise information is examined [e.g., fluctuation of noise levels or frequency distribution (Hz)]. Fourth, although we did collect information on the direction of the child's bedroom window for the LISAplus cohort, we did not collect information on window opening habits, which may be a key factor in this study. For example, it is possible that people are exposed to higher levels of noise when they leave the windows open at night during warm periods. [12] Furthermore, due to the small number of children who have information on the windows direction (N = 197 in LISAplus), we were unable to directly explore the interaction between noise levels and the window direction in our models. Fifth, as previously mentioned, exposure misclassification is a concern in these types of studies. The noise levels used in this study are outdoor noise levels within a 50 m buffer of the child's home, without considering directionality. Thus, it is not clear if the assigned noise level (maximum or minimum) is the noise level actually outside of the child's bedroom. It is possible that a child with a high maximum noise level may actually be sleeping in a quieter part of the house, and thus the noise exposure would be overestimated (and vice versa). It is quite conceivable that the maximum noise level registered in our study is away from the child's bedroom (for example, in front of the house), which may explain why we did not observe an association between Lnight_max and blood pressure. Furthermore, 10-year-old children spend most of their time at school, thus noise levels at home might not reflect a child's actual daytime exposure. This type of exposure misclassification may have contributed to the lack of association between Lden_max/Lden_min and SBP observed in this study. This lack of association with noise exposures assessed at the home address has also been documented by others. For example, Regecova and Kellerova [5] found that children's SBP was significantly associated with noise levels at schools but not at residences. Evans et al. [10] also reported non-significant differences in SBP in children exposed to low compared to high noise levels at residences.

Despite the limitations, this study also has important strengths. Firstly, this study is unique in examining the association between blood pressure and individual noise exposure levels during night time. Night-time noise has only been considered by two other studies, which dichotomized noise levels into noisy and quiet areas. [20] Secondly, this study is one of the few studies that have considered the direction of the child's bedroom window in the analyses. To our knowledge, only one other recently published paper [24] has incorporated this factor in their analyses. Belojevic and Evans studied the effects of traffic noise on blood pressure among 250 African-American children of low-socioeconomic status, aged 6-14 years. They found no significant effect of noise exposure at home/school on blood pressure [for SBP, β (95% CI) = 0.0007 (-0.003, 0.004); for DBP, β (95% CI) = 0.0009 (-0.004, 0.002)]. When examining the impact of the orientation of the child's bedroom and living room on these associations, no interaction with noise at home was found on blood pressure [for SBP, β (95% CI) = -0.007 (-0.053, 0.038); for DBP, β (95% CI) = 0.011 (-0.026, 0.047)].

The World Health Organization [25] has recognized noise as an important factor that may affect health, and previous epidemiological studies have provided evidence to support this claim, as do the results of our current study. Although it is unclear how the long-term effects of early noise exposure may affect the cardiovascular systems of children, it is conceivable that noise-induced elevations of blood pressure may cause adverse effects later in their life. [9],[26]

In order to better understand the association between noise and blood pressure in children, we recommend that future studies pay particular attention to the exposure assessment; noise exposure should be assessed at kindergartens and schools during daytime and at the home residence at night. In addition, the direction of the bedroom window should be considered as a potential factor in future studies, especially given the strong associations with this covariate documented in this study.

  Conclusions Top

The results of this study suggest that road traffic noise may increase blood pressure in children, especially DBP. The level of minimum noise at home appears to be important. Our finding that the direction of the child's bedroom affects the modeled estimates highlights the importance of including this factor in future studies.

  References Top

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Correspondence Address:
Chuang Liu
Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology I, Neuherberg; Faculty of Medicine, Ludwig-Maximilians-University of Munich, Munich, Germany

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1463-1741.112364

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  [Figure 1]

  [Table 1], [Table 2], [Table 3]

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[Pubmed] | [DOI]
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[Pubmed] | [DOI]