Indoor noise exposure at home: a field study in the family of urban schoolchildren

Environmental noise, brain structure, and language development in children

While excessive noise exposure in childhood has been associated with reduced language ability, few studies have examined potential underlying neurobiological mechanisms that may account for noise-related differences in language skills. In this study, we tested the hypotheses that higher everyday noise exposure would be associated with 1) poorer language skills and 2) differences in language-related cortical structure. A socioeconomically diverse sample of children aged 5-9 (N = 94) completed standardized language assessments. High-resolution T1-weighted magnetic resonance imaging (MRI) scans were acquired, and surface area and cortical thickness of the left inferior frontal gyrus (IFG) and left superior temporal gyrus (STG) were extracted. Language Environmental Analysis (LENA) was used to measure levels of exposure to excessive environmental noise over the course of a typical day (n = 43 with complete LENA, MRI, and behavioral data). Results indicated that children exposed to excessive levels of noise exhibited reduced cortical thickness in the left IFG. These findings add to a growing literature that explores the extent to which home environmental factors, such as environmental noise, are associated with neurobiological development related to language development in children.

The Negative Impact of Noise on Adolescents' Executive Function: An Online Study in the Context of Home-Learning During a Pandemic

UNICEF estimates that 1.6 billion children across the world have had their education impacted by COVID-19 and have attempted to continue their learning at home. With ample evidence showing a negative impact of noise on academic achievement within schools, the current pre-registered study set out to determine what aspects of the home environment might be affecting these students. Adolescents aged 11-18 took part online, with 129 adolescents included after passing a headphone screening task. They filled out a sociodemographic questionnaire, followed by a home environment and noise questionnaire. Participants then completed three executive function tasks (the Flanker, the Backward Digit Span, and the Wisconsin Card Sorting Test) while listening to a soundtrack of either white noise or home-like environmental noise. For purposes of analysis, based on the noise questionnaire, participants were separated into quieter and noisier homes. Results revealed that measures of the home environment significantly correlated with individual perceptions of noise and task performance. In particular, adolescents coming from noisier homes were more likely to report that they studied in a noisy room and that they were annoyed by noise when studying. In terms of noise and task performance, the Flanker task revealed that while older adolescents were more efficient overall than their younger peers, those older adolescents from noisier homes seemed to lose this advantage. Additionally, reaction times for younger adolescents from noisier homes were less impacted by accuracy compared to their peers from quieter homes, though there was no difference for the older adolescents. This evidence suggests that higher in-home noise levels lead to higher rates of annoyance and may be hindering home-learning, with both younger and older adolescents being impacted. Furthermore, the long-term effect of in-home noise on adolescent executive function task performance indicates that these findings transcend the pandemic and would influence in-school learning. Limitations and advantages of online adolescent research without researcher supervision are discussed, including sociodemographics and adapting tasks.

Association between moderated level of air pollution and fetal growth: the potential role of noise exposure

This study aims to analyze, in a population of singletons, the potential confounding or modifying effect of noise on the relationship between fetal growth restriction (FGR) or small for gestational age (SGA) and environmental exposure to air pollution. All women with single pregnancies living in one of two medium-sized cities (Besançon, Dijon) and who delivered at a university hospital between 2005 and 2009 were included. FGR and SGA were obtained from medical records. Outdoor residential exposure to nitrogen dioxide (NO₂) and particulate matter (PM₁₀) was quantified at the mother’s address at delivery over defined pregnancy periods; outdoor noise exposure was considered to be the annual average daily noise levels in the façade of building (L_{Aeq,24 h}). Adjusted odds ratios (OR_a) were estimated by multivariable logistic regressions. Among the 8994 included pregnancies, 587 presented FGR and 918 presented SGA. In the two-exposure models, for SGA, the OR_a for a 10-µg/m³ increase of PM₁₀ during the two last months before delivery was 1.18, 95%CI 1.00–1.41 and for FGR, these OR_a were for the first and the third trimesters, and the two last months before delivery: 0.77 (0.61–0.97), 1.38 (1.12–1.70), and 1.35 (1.11–1.66), respectively. Noise was not associated with SGA or FGR and did not confound the relationship between air pollution and SGA or FGR. These results are in favor of an association between PM₁₀ exposure and fetal growth, independent of noise, particularly towards the end of pregnancy, and of a lack of association between noise and fetal growth.

Noise Annoyance in Urban Children: A Cross-Sectional Population-Based Study

Acoustical and non-acoustical factors influencing noise annoyance in adults have been well-documented in recent years; however, similar knowledge is lacking in children. The aim of this study was to quantify the annoyance caused by chronic ambient noise at home in children and to assess the relationship between these children's noise annoyance level and individual and contextual factors in the surrounding urban area. A cross sectional population-based study was conducted including 517 children attending primary school in a European city. Noise annoyance was measured using a self-report questionnaire adapted for children. Six noise exposure level indicators were built at different locations at increasing distances from the child's bedroom window using a validated strategic noise map. Multilevel logistic models were constructed to investigate factors associated with noise annoyance in children. Noise indicators in front of the child's bedroom (p ≤ 0.01), family residential satisfaction (p ≤ 0.03) and socioeconomic characteristics of the individuals and their neighbourhood (p ≤ 0.05) remained associated with child annoyance. These findings illustrate the complex relationships between our environment, how we may perceive it, social factors and health. Better understanding of these relationships will undoubtedly allow us to more effectively quantify the actual effect of noise on human health.

Individual daytime noise exposure in different microenvironments

BACKGROUND

Numerous studies showed that chronic noise exposure modeled through noise mapping is associated with adverse health effects. However, knowledge about real individual noise exposure, emitted by several sources, is limited.

OBJECTIVES

To explain the variation in individual daytime noise exposure regarding different microenvironments, activities and individual characteristics.

MATERIALS AND METHODS

In a repeated measures study in Augsburg, Germany (March 2007-December 2008), 109 individuals participated in 305 individual noise measurements with a mean duration of 5.5h. Whereabouts and activities were recorded in a diary. One-minute averages of A-weighted equivalent continuous sound pressure levels (Leq) were determined. We used mixed additive models to elucidate the variation of Leq by diary-based information, baseline characteristics and time-invariant variables like long-term noise exposure.

RESULTS

Overall noise levels were highly variable (median: 64 dB(A); range: 37-105 dB(A)). Highest noise levels were measured in traffic during bicycling (69 dB(A); 49-97 dB(A)) and lowest while resting at home (54 dB(A); 37-94 dB(A)). Nearly all diary-based information as well as physical activity, sex and age-group had significant influences on individual noise. In an additional analysis restricted to times spent at the residences, long-term noise exposure did not improve the model fit.

CONCLUSIONS

Individual exposures to day-time noise were moderate to high and showed high variations in different microenvironments except when being in traffic. Individual noise levels were greatly determined by personal activities but also seemed to depend on environmental noise levels.

Pilot study of methods and equipment for in-home noise level measurements

Knowledge of the auditory and non-auditory effects of noise has increased dramatically over the past decade, but indoor noise exposure measurement methods have not advanced appreciably, despite the introduction of applicable new technologies. This study evaluated various conventional and smart devices for exposure assessment in the National Children's Study. Three devices were tested: a sound level meter (SLM), a dosimeter, and a smart device with a noise measurement application installed. Instrument performance was evaluated in a series of semi-controlled tests in office environments over 96-hour periods, followed by measurements made continuously in two rooms (a child's bedroom and a most used room) in nine participating homes over a 7-day period with subsequent computation of a range of noise metrics. The SLMs and dosimeters yielded similar A-weighted average noise levels. Levels measured by the smart devices often differed substantially (showing both positive and negative bias, depending on the metric) from those measured via SLM and dosimeter, and demonstrated attenuation in some frequency bands in spectral analysis compared to SLM results. Virtually all measurements exceeded the Environmental Protection Agency's 45 dBA day-night limit for indoor residential exposures. The measurement protocol developed here can be employed in homes, demonstrates the possibility of measuring long-term noise exposures in homes with technologies beyond traditional SLMs, and highlights potential pitfalls associated with measurements made by smart devices.