Average Noise Level Research Articles

Assessing indoor and outdoor noise quality and associated health impacts at selected schools in Surat, India

An optimal ambient environment is crucial for healthy development, yet the excess of vehicles and inadequately planned educational infrastructures compromise cognitive growth in children. This study evaluates the impact of ambient noise on student cognition in five schools situated along city arterial and sub-arterial roads. A total of 717 students from grades 7, 8, 9, and 11 participated. Noise levels were measured in prevailing noisy conditions (PC) and controlled silence conditions (SC) within classrooms using the Kimo dB300 sound level meter. The observed differences in noise levels between PC and SC varied across grades, showing reductions of 4.7 ± 3.5 dB, 6.1 ± 0.7 dB, 6.7 ± 1.3 dB, and 4.4 ± 3.46 dB for grades 7, 8, 9, and 11, respectively. Statistical analyses revealed significant differences in the average noise levels under both conditions. Furthermore, cognitive task performance in PC and SC was significantly different, as evidenced by paired t-tests in tasks such as multiplication, word formation, reasoning, and sentence construction. Dimension reduction techniques identified room acoustics, task difficulty, speech intelligibility, mental deficiency, and annoyance as critical factors affecting learning abilities. Teachers reported that major impacts of noise include annoyance, sleeplessness, headache, and hearing impairment.

The challenges of mapping quiet urban areas from mobile sound surveys

Detailed spatial data on noise levels are needed to identify quiet areas. Yet noise maps derived from sound propagation models based on traffic flows or sensor networks are often incomplete. Surveys using mobile sound recording coupled with machine learning modelling have offered a possible solution, but so far have focused on averaged noise levels. We argue that quiet areas should ideally be consistently quiet, rather than simply quiet on average, yet mobile survey data usually lack the full temporal profile needed to quantify consistency in noise levels. Using data from our Southampton study area, we show that modification of the loss function used in machine learning modelling of mobile survey data can yield information on the likely range of noise levels at any location across an entire city. We use this approach not only to identify locations that are consistently quiet, but also to help understand which urban features may be associated with quiet, average and noisy events at any given location.

Noise emission characteristics of cosmetics manufacturing plants

Recently, a rapid increase in the establishment of cosmetics manufacturing facilities has been observed in Korea because of the growing export of K-beauty products. Many of these factories are certified under good manufacturing practice (GMP) standards and show significant interest in quality management, industrial injury prevention, and productivity enhancement. Among industrial injuries, noise-induced hearing loss holds the largest share, rendering it crucial for industrial injury prevention. Therefore, this study aimed to assess the noise exposure status in cosmetics manufacturing facility spaces. Analysis revealed that the 24-h average continuous noise level (L_eq) was approximately 69.0 dB(A). The measured areas were divided into three rooms based on their purpose, of which the Manufacturing Room showed the highest noise levels ranging from 74.0 to 77.0 dB(A). Additionally, the Blister Packaging and Sealing Room ranged from 64.1 to 66.1 dB(A), and the Box Packing Room ranged from 64.3 to 65.8 dB(A), all within acceptable limits and not exceeding day-night noise correction exposure standards. From the perspective of industrial injury prevention and monitoring, this study aims to implement these measurement results within the metaverse in the future for visualization.

Noise modeling of UAM around the urban vertiport

The present study aims to investigate the noise distribution around urban vertiport caused by UAM(Multicopter) and helicopter. Noise modelings were carried out using SoundPLAN software at the some vertiports in Seoul, Korea. Sound source model of UAM and helicopter were used as a form of hemisphere. Noise predictions were undertaken with three different operations including depart, level flight and landing. In order to evaluate the noise impact on the buildings around the vertiport, noise levels at the outer wall of nearby buildings were calculated as the three noise units including Leq, Lmax and Lden. Also, noise maps were drawn around the vertiport. As a result, it was found that average noise level of UAM is approximately 12 dB lower than the helicopter noise levels. Regarding the noise frequency distribution, most high noises are made at the mid-frequencies during landing hours while low frequency noise level around 63 Hz was dominant at take-off time.

Cologne ergonomic measurement for robotic surgery (CEMRobSurg) using the Hugo™ RAS System.

The ergonomic advantages and potential challenges that robotic surgery poses to the well-being of surgeons are mainly unexplored. The most recent surgical robot introduced on the European market is the Hugo™ RAS System by Medtronic. This study aims to evaluate the ergonomic benefits of the Hugo™ RAS System, which is available in our training laboratory, CeMIT (Center for Medical Innovation and Technology Cologne). Using the previously established Cologne Ergonomic Measurement Setup for Robotic Surgery (CEMRobSurg), we measured three parameters related to ergonomic posture from subjects with different levels of surgical expertise (laypeople, medical students, surgical residents, and expert robotic surgeons). The heart rate was measured continuously using a polar band. The noise level was measured while using the Hugo™ RAS System, and automated photographs using our locally developed methodology were captured of the participant every 2s to assess body posture. The ergonomic measurements were conducted while the subject performed the same standardized robotic training exercises (Peg Board, Rope Walk, and Ring Walk). A total of 53 participants were enrolled in this study. The average noise level during all measurements was 54.87 dB. The highest stress level was measured in surgical residents with a sympathetic nervous system index (SNS index) of 1.15 (min - 1.43, max 3.56). The lowest stress level was measured in robotic experts with an SNS index of 0.23 (min - 0.18, max 0.91). We observed a risk-prone positioning of the neck and elbow in medical students (mean 39.6° and 129.48°, respectively). Robotic experts showed a risk positioning in the knee and hip region (mean 107.89° and 90.31°, respectively). This is the first study to analyze and objectify the ergonomic posture of medical students, surgical trainees, surgeons, and laypeople using the open console, modular Hugo™ RAS System. Our findings offer recommendations for operating surgeons and allow for a comparative analysis between the different robotic systems. Further evaluations in real-time operative scenarios will follow.

Perbandingan Tingkat Kebisingan Berbagai Bahan Peredam pada Knalpot Sepeda Motor Racing

The use of racing exhausts on motorised vehicles can cause uncomfortable and dangerous noise pollution if it exceeds the threshold set by the Minister of Environment. Based on the Decree of the Minister of Environment No 07/2009, the noise limit for motorbikes with engine capacity below 80 cc is 77 dB, 80-175 cc is 80 dB, and above 175 cc is 83 dB. This study aims to observe the comparison of noise levels of various silencer materials on racing motorbike exhausts in order to find the most effective material in reducing noise in accordance with these regulations. The noise measurement method follows the ISO 5130 standard, carried out when the engine is running idle and at engine speed range from 0 to 8000 RPM with a variety of different damping materials. The results show that at idle conditions, yellow Glasswool is the best damping material with the lowest noise level of 90.31 dBA, while Stainless wool shows the worst performance with an average noise level of 100.81 dBA. In contrast, in the 0-8000 RPM rotation condition, Stainless wool became the most superior silencer material with a noise level of 105.4 dBA, while grandma's hair Glasswool (fibreglass) became the worst with the highest noise level of 106.4 dBA. The conclusion of this study is that the optimal choice of silencer material can differ depending on the operating conditions of the racing exhaust, with yellow Glasswool being more effective at idle conditions and Stainless wool being more effective at maximum revs.

Noise in operating theatres, is it safe?

Noise-Induced Hearing Loss (NIHL) is a condition caused by repeated exposure to loud noise, with operating theatre personnel potentially at risk. The aims of this study were to establish the typical noise levels in orthopaedic theatres and to compare these to The Control of Noise at Work Regulations 2005. We measured the average noise levels in 40 trauma and orthopaedic surgeries in a single centre. We used the Decibel X app to take measurements, then performed corrections to ascertain noise levels at the surgeon's ear (Leq). The daily noise exposure level for theatre staff for each procedure (LEP, d) and the LEP, d over an average 8-hour working day when performing different groups of procedures were calculated. Data were analysed using descriptive statistics, ANOVA, t-test and the Pearson coefficient of correlation. The LEP, d lower action value (80 dBA) as set by the Health and Safety Executive (HSE) was met by performing a single revision total knee replacement or a right open ankle debridement. Assuming three procedures are conducted per list, lists consisting of joint replacements (82 dBA) or medium elective procedures (81 dBA) exceed this lower limit. Additionally, lists comprising large and medium bone fractures would be within 1 dB of the limit (79 dBA and 79 dBA, respectively). Soft tissue (74 dBA), arthroscopic (73 dBA), and small bone fracture (71 dBA) procedures had the lowest LEP, d. The greatest contributors to noise levels were surgical instruments. The number of people in the room made a significant difference to noise levels (p = 0.032). We have established the baseline noise levels in various orthopaedic procedures. Measures should be taken to meet UK regulations. Further research should determine suitable measures for protection from hearing damage for theatre staff and evaluate the risks high noise levels pose to patients.

Reducing Noise in the NICU.

In the neonatal intensive care unit (NICU), elevated noise negatively impacts the neurodevelopmental environment, interrupts sleep, and can affect brain development in neonates. The American Academy of Pediatrics recommends that noise levels in the NICU should not exceed 45dB. The project aims were to: (1) decrease average noise level by 10% from baseline and (2) decrease exposure to severe noise (>65dB) to <5% of the time. This quality improvement project was conducted during 2021-2022 as a pre/post observational design in a Level IV NICU in New York City. We monitored sound levels for 20-24h, 5d/wk. Quality improvement interventions included: novel approaches to staff education, visual cues for when noise thresholds were exceeded, parent education, including access to personal decibel meters, technical improvements to vital sign monitors and entry doors, and defined quiet times (HUSH) for 2h each 12-hour shift. Education efforts and technical improvements successfully reduced median noise levels within the stepdown unit ( P <.001), though not in the acute care NICU. In contrast, the implementation of 2-hour periods of enforced "quiet time" every 12h effectively reduced both median noise levels and the incidence of severe noise (>65dB) in both locations. The HUSH strategy may be a sustainable way to decrease noise in the NICU. Future projects should prioritize education and dedicated quiet times to align with recommended standards, while research should explore the long-term developmental impacts of excessive noise levels on neonatal growth.

Design optimization of floor plan for public housing buildings in Hong Kong with consideration of natural ventilation, noise, and daylighting

Indoor environmental quality plays a crucial role in determining the overall quality of life. This study aims to develop a design optimization approach for the floor plan of public housing buildings with modular flat design in Hong Kong, with focus on enhancing natural ventilation, reducing noise levels, and improve daylighting conditions. The evaluation of these environmental factors was conducted using deep neural network models and a mathematically based Calculation of Road Traffic Noise model. A general floor plan representation was developed for three- and four-winged structures of public housing buildings. An optimization approach utilizing Bayesian optimization was applied to three studied cases: Hung Shing House, Hung Hei House, and Cheung Tai House. The optimization process resulted in an average 41.5 % improvement in average natural ventilation rate. The optimized building shapes effectively served as noise barriers, leading to an average reduction of 20 % in average noise levels. The existing window configurations of each unit type under the modular flat design already provided sufficient daylighting, resulting in only a minor improvement from the optimization process.

Sustaining tranquility in small urban green parks: A modeling approach to identify noise pollution contributors

Noise pollution poses a significant environmental challenge in Iranian urban areas, particularly within Small Urban Green Parks (SUGPs). This study investigates the extent of noise pollution in SUGPs and identifies key contributors to elevated noise levels. A total of 94 SUGPs, with a mean area of 1.86 ± 0.99 hectares, were selected in Isfahan City, Central Iran, and subjected to 30-m Equivalent Sound Level (Lq30) measurements at their central locations. Explanatory variables were classified into two categories based on road density, traffic volume, proximity to roads, park vegetation, and physical characteristics. The relationship between noise levels and each explanatory variable was observed to be non-linear and polynomial (R2 < 0.334) in certain instances. Our modeling results using the Multi-Layer Perceptron (MLP)-Artificial Neural Network (ANN) model (R2 = 0.936) indicate that average noise levels in these parks surpass international guidelines, averaging 65.97 ± 17.76 dB. Traffic volume and proximity to limited access roads were identified as primary factors influencing noise levels in SUGPs. It was observed that the design and layout of small urban parks may not effectively mitigate surrounding traffic noise, even with sufficient green barriers to absorb or block sound. Consequently, future efforts should prioritize strategic site selection for SUGPs to minimize exposure to major noise sources.

Assessing wayside traffic noise levels using long-term noise monitoring and available Department of Transportation traffic data - worst-case noise traffic conditions, effects of repaving, and methods for comparing traffic noise data sets

The availability of automated continuous traffic data from State Departments of Transportation (DOTs), such as the California Department of Transportation (Caltrans) Performance Measurement System (PeMS), provides increased opportunities for the analysis of highway noise. Traffic data that is free to access and downloadable via the internet can be matched with unattended long-term noise measurement data to provide large datasets for analysis, without requiring field staff to be continuously on site. A 2018 ICF/Caltrans paper documented how this approach was used on an operating freeway to determine the volume of traffic that results in the highest one-hour energy average traffic noise level. At the time of those measurements, the subject freeway had Portland cement concrete pavement. The freeway has since been repaved with an open-graded rubberized asphalt concrete pavement overlay. The current study uses new (2023) traffic noise measurements and PeMS data to investigate how worst-noise conditions have changed and the effect of the repaving on wayside noise levels. Changes in traffic patterns since 2018 required the authors to normalize the measurement data for comparison. Opportunities were identified to take advantage of the large measurement data sets to match before-and-after data, and those methods are also described in this paper.

Evaluation of Sound Pollution Near Several Government and Private Hospitals in Najaf City

One notable aspect of the environment is sound pollution, which varies in intensity depending on where it comes from, it has varied degrees of impact on the nearby buildings and items like Hospitals are exposed to noise. Additionally, because most hospitals are situated on major thoroughfares, industrial activities and commercial activities. As a result, these structures are frequently subjected to high levels of environmental noise due to the work and care that hospitals give for their patients, which necessitates relaxation and tranquility. The purpose of this study is to determine how much noise pollution in the area around multiple hospitals in Najaf City is caused by various activities. An equipment known as the Sound degree Meter (IEC 61672-1 type 2) was utilized to measure the degree of noise pollution , three times a day—Sunday, Tuesday, and Thursday—during a period of four weeks, the months of June and July were used to measure the noise levels. These measurements were also made in the vicinity of the hospitals—three times in the morning, afternoon, and evening. According to the World Health Organization and Iraqi Determinants of Noise, the average noise levels measured outside the hospital on certain days were significantly higher than the environmental noise limit required. Ultimately, several recommendations for lowering the noise level in this vicinity were made.

Air Quality Assessment in Petroleum Flow Station: A Case Study of Oredo Flow Station

Air quality is a vital aspect of environmental health and a key determinant of human wellbeing. This study was carried out to assess air quality parameters and noise levels around Oredo Flow Station in Edo State, Nigeria. Parameters measured during the study were temperature, suspended particulate matter (SPM), sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and noise. Each parameter was measured using appropriate equipment. Measurements were done at three points: Point A (300m from the flare site), Point B (200m from the flare site) and Point C (100m from the flare site) and in triplicates with mean values recorded. The result showed that temperature ranged from 28.60±0.3°C to 29.22±0.3°C; SPM ranged from 17.16±3.9 μg/m3 to 60.74±14.6 μg/m3 ; SO2 ranged from 0.01±0.0 ppm to 0.03±0.0 ppm; CO concentrations ranged from 0.03±0.0 ppm to 4.45±1.3 ppm; and VOC concentrations ranged from 0.01±0.0 ppm to 1.87±0.2 ppm. The mean noise levels ranged from 56.24±2.8dB to 87.78±2.8dB. Time-weighted average noise level ranged from 56.2dB to 87.8dB. For all parameters, there was a general decreasing trend in values as distance to the flare site increased indicating that air quality parameters in the area were influenced by gas flaring activities. Recommendations made include routine air quality monitoring, alternative use of natural gas and implementing noise control measures.

Assessing the ecological impact of industrial noise pollution on wildlife behavior in Okomu Forest Reserve, Nigeria

The study identified sources and established the levels of industrial noise in Okomu National Park with the aim of determining the impact of industrial noise pollution on wildlife in Okomu National Park. It also modelled propagation of ambient noise levels associated with the established levels as well as determined impacts of ambient noise obtained from industrial activities on wildlife of the National Park. Locations of identified sources of noise including industrial activities sources relative to the National Park were established and digital maps of the identified locations was generated. Ambient noise levels were obtained for wildlife populations around selected locations. Noise assignment was done at each of the hotspots for industrial activity that had been detected using EXTEC sensors. The average noise levels from the industrial sources were then processed into a model using NoiseMap. The calculated noise levels from identified sources were represented with contour map. The results identified sources of noise pollution in Okomu Forest Reserve as: Okomu Palm Oil processing mill and Michelin rubber Processing factory. The result showed that activities within these industries produced at least 40 dB during the period of study. The effects of noise from the industrial activities forced the migration of the animals out of the National Park to favourable habitats with less noise sources. The retreat of the animals caused energy depletion and reduced the chances of their survival. The study concluded that industrial activities such as Palm oil processing, rubber processing, logging and vehicles are a major source of noise pollution that threatens the sustainability of wildlife in the Okomu National Park.

Noise Pollution Assessment, Spatial Noise Mapping and Associated Health Impacts in Dinajpur City, Bangladesh

Noise pollution is one of the more prevalent types of pollution caused mainly by urbanization. It is characterized as noise propagating throughout a living being in a way that is to its physical and mental health. Along with the growth of the city, trade, business, shopping, education, and other activities have been accelerating. The main purpose of the study was to address the dangerous point of noise pollution in Dinajpur municipality and identify the causes of noise pollution. For this study, data sets on the amount of noise pollution at 35 different places throughout Dinajpur city have been analyzed. Three shifts of data collection were conducted: morning (8 am to 10 am), afternoon (12 pm to 2 pm) and evening (4.00 pm-6.00 pm). Using the ArcGIS 10.8 program, descriptive statistics tools and analysis of variance were carried out. The highest average noise level (105.7 dB) was found at Central Bus Terminal at the time of evening which is a mixed zone. The lowest average noise level (64 dB) was found at Chotogurgola and Balubari at the time of morning and evening respectively which is residential zone. The noise levels throughout the city vastly exceed both the WHO and DoE recommendations. The main causes of noise pollution are the expanding urban area, unregulated auto rice mills establishment, the heavy use of construction equipment, automobile engines, uncontrolled horns, and outrageous auto rickshaws etc. It is vital to take action to lower noise levels because prolonged exposure to noise has numerous negative effects. The development of comprehensive land use plans for this city would benefit from taking noise pollution into consideration.

Prevalence and associated factors of noise-induced hearing loss among workers in Bishoftu Central Air Base of Ethiopia

Excessive occupational exposure to noise results in a well-recognized occupational hearing loss which is prevalent in many workplaces and now it is taken as a global problem. Therefore, this study aims to assess the prevalence of noise-induced hearing loss and associated factors among workers in the Bishoftu Central Air Base in Ethiopia. An institutional-based cross-sectional study was conducted among 260 central air base workers through face-to-face interviews, an environment noise survey, and an audiometric test for data collection. Data were entered by Epi-data version 3.1 and SPSS was used to analyze the data. Finally, a statistical analysis such as descriptive and binary logistic regression analysis was applied. A P-value < 0.05 at 95% CI was considered statistically significant. The overall prevalence of noise-induced hearing loss and hearing impairments was 24.6 and 30.9%, respectively. The highest prevalence of noise-induced hearing loss was recorded for workers who were exposed to noise levels greater than 90 dBA. Out of 132 workers exposed to the average noise level of 75 dB A, only 5% of workers were affected with noise-induced hearing loss, while 128 workers exposed to an average noise level equal to or greater than 90 dB A, 19.6% of workers were identified with noise-induced hearing loss. Regarding sex, around 21.9% of male workers were identified with noise-induced hearing loss. Workers who were exposed to a high noise level workplace previously or before the Central Air Base workplace were five times (AOR = 5.0, 95% CI 1.74–14.36) more likely affected by noise-induced hearing loss than those workers not previously exposed. Those workers who were exposed to greater or equal to 90dBA noise level were 4.98 times (AOR = 4.98, 95% CI 2.59–9.58) more likely to be exposed to noise-induced levels than those who were exposed to less than 90dBA noise level. Moreover, male air base workers were 3.5 times more likely exposed to hearing impairment than female workers (AOR = 3.5, 95% CI 1.01–12.0). This study identified that the prevalence of noise-induced hearing loss and hearing impairments was significantly high. So implementation of a hearing conservation program, giving noise education, and supplying adequate hearing protective devices (HPDs) are essentials.

The effect of developmental care on the length of hospital stay and family centered care practice for very low birth weight infants in neonatal intensive care units: A cluster randomized controlled trial

BackgroundDespite previous studies suggesting that developmental care can provide benign stimulation to promote neural development of newborns, more evidence is needed regarding the other clinical benefits of developmental care. ObjectiveTo evaluate the effect of implementing developmental care on the length of hospital stay, the improvement of care practice in neonatal intensive care units, as well as the short-term outcome of very low birth weight infants. DesignCluster-randomized controlled trial. Setting(s) and participantsFrom March 1, 2021 to March 1, 2022, 1400 very low birth weight infants were recruited from 14 tertiary neonatal intensive care units in China. MethodsWe assigned 14 neonatal intensive care units to either developmental care or standard care. The length of hospital stay of the infants was the primary outcome analyzed at the individual level. Secondary outcomes were family centered care practice including parental involvement, the skin to skin care, exclusive breast milk, oral immune therapy and breastfeeding. The environmental management (noise and light) and the short-term outcomes were also evaluated. ResultsThe length of hospital stay for the developmental care group was 65 % as long as that for the control group (HR: 0.65, 95 % CI, 0.451–0936, p = 0.021). After controlling the covariables, the adjusted HR = 0.755 (95 % CI, 0.515 to 1.107, p = 0.150). When compared to the control group, the developmental care group had greater access to SSC, with 22 infants (3.8 %) in the developmental care group compared to 13 infants (1.7 %) in the standard care group (p = 0.013). A greater proportion of infants in the developmental care group were fed at the breast, than those in the standard care group (136 [23.6 %] vs 9 [1.1 %]; p = 0.029). Compared to the control group, exclusively breast milk was significantly more favorable in the developmental care group (435 [75.6 %] vs 114 [15.0 %]; p = 0.001). The difference remained significant even after adjusting for covariates. However, the rate of oral immune therapy and parental involvement was similar in the two groups. The average noise and light levels in the developmental care group were significantly lower than those in the standard care group. After adjusting for confounders, the difference remained significant. There were no significant differences among groups in the mortality and major morbidity. ConclusionsDevelopmental care might have developed an accumulated effect over time on the length of hospital stay among very low birth weight infants. The implementation of developmental care can greatly improve family centered care practices and the neonatal intensive care unit environment. RegistrationClinicalTrials.govNCT05166720. Registration date: 1 March, 2021.

Prediction of Noise Level in Ota Metropolis Using Artificial Neural Network

Capturing noise data is laborious, time-consuming, expensive and dangerous due to the exposure of the investigator to the menace. Also, appropriate software, computational skill and computational time are also required before the captured data could be of any use. In this work, an artificial neural network (ANN) was deployed to learn and train noise data in Ota Metropolis. Data were captured from forty-one (41) locations for the morning, afternoon and evening in Ota Metropolis. ANN with Levenberg Marquardt algorithm and architectural configuration of 2-21-9 (input-hidden neuron-output) was used to predict noise descriptors for Ota Metropolis with 73% accuracy. The two input variables were the latitude and longitude of the location measured in degrees while the nine output variables are the noise descriptors such traffic noise index (TNI), noise pollution level (LNP), and average equivalent noise levels (LAeq) computed for each selected location for morning, afternoon and evening periods. The results could be used in mobile applications, Google Earth and other platforms to guide residence dwellers, travellers, industrialists and technocrats in selecting travelling routes, choice of apartment location and use of appropriate personal protective equipment (PPE) in unavoidable noisy locations.

Evaluation of noise levels and noise sources in an Irish neonatal intensive care unit.

This study: (i) quantified the typical noise levels in an Irish neonatal intensive care unit (NICU) and compared the values to recommendations by the American Academy of Paediatrics (AAP) and the European Standards for Care for Newborn Health (EFCNI) and to occupational exposure limit value and exposure action values; and (ii) qualified the perception of noise levels and the sources of noise across the various stakeholders within a typical NICU. A noise survey was conducted in an Irish NICU. Observations identified practices and behaviours in the NICU that potentially had an impact on noise levels. Noise levels were compared to occupational exposure limits and AAP and EFCNI standards. A noise perception survey was conducted to identify noise sources and awareness of noise levels in the NICU. Results were analysed using SPSS Statistics to determine statistical significance. Noise levels recorded were consistent with previous similar studies and in all cases, the average noise levels recorded exceeded the 45 dBA as recommended by the AAP and EFCNI. There was a statistically significant difference (P < 0.01) between noise levels recorded on the day shift compared to the night shift. The perception of noise levels reported by nurses versus parents was found to be statistically significant (P = 0.001). 38.3% of all respondents reported having received no information or training with regard to noise in the NICU. There was a statistically significant difference in the perception of who is most likely to be affected by noise in the NICU, with nurses reporting those most likely to be affected by noise were patients, and parents reporting those most likely to be affected were staff (P = 0.003). This study supports the hypothesis that noise levels within the NICU are of concern and require regular assessment and monitoring. Training and awareness programmes are an important component to ensuring all persons in the NICU recognise their potential impact on noise levels in the NICU and in reducing the risk for patients and staff.

Aircraft noise exposure and body mass index among female participants in two Nurses’ Health Study prospective cohorts living around 90 airports in the United States

ObjectiveAircraft noise exposure is linked to cardiovascular disease risk. One understudied candidate pathway is obesity. This study investigates the association between aircraft noise and obesity among female participants in two prospective Nurses’ Health Study (NHS and NHSII) cohorts. MethodsAircraft day-night average sound levels (DNL) were estimated at participant residential addresses from modeled 1 dB (dB) noise contours above 44 dB for 90 United States (U.S.) airports in 5-year intervals 1995–2010. Biennial surveys (1994–2017) provided information on body mass index (BMI; dichotomized, categorical) and other individual characteristics. Change in BMI from age 18 (BMI18; tertiles) was also calculated. Aircraft noise exposures were dichotomized (45, 55 dB), categorized (<45, 45–54, ≥55 dB) or continuous for exposure ≥45 dB. Multivariable multinomial logistic regression using generalized estimating equations were adjusted for individual characteristics and neighborhood socioeconomic status, greenness, population density, and environmental noise. Effect modification was assessed by U.S. Census region, climate boundary, airline hub type, hearing loss, and smoking status. ResultsAt baseline, the 74,848 female participants averaged 50.1 years old, with 83.0%, 14.8%, and 2.2% exposed to <45, 45–54, and ≥55 dB of aircraft noise, respectively. In fully adjusted models, exposure ≥55 dB was associated with 11% higher odds (95% confidence interval [95%CI]: −1%, 24%) of BMIs ≥30.0, and 15% higher odds (95%CI: 3%, 29%) of membership in the highest tertile of BMI18 (ΔBMI 6.7 to 71.6). Less-pronounced associations were observed for the 2nd tertile of BMI18 (ΔBMI 2.9 to 6.6) and BMI 25.0–29.9 as well as exposures ≥45 versus <45 dB. There was evidence of DNL-BMI trends (ptrends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers. DiscussionIn two nationwide cohorts of female nurses, higher aircraft noise exposure was associated with higher BMI, adding evidence to an aircraft noise-obesity-disease pathway.