Exploring the relationship between of environmental noise and sleep using HowLoud inc. Soundscores

Abstract

This study seeks to understand the environmental noise experienced at subjects' home addresses in a sleep study. Environmental noise, often caused by human activities, significantly affects home values, businesses, and health. The health impacts of noise include disturbed sleep, stress, and anxiety. Unfortunately, collecting, modeling, and mapping environmental noise is challenging. Direct noise measurement relies on acoustic sensing devices, but ground-based devices like transportation noise meters have limitations, especially outside urban areas. Models, such as the Federal Highway Administration Traffic Noise Model and Federal Aviation Administration Aviation Environmental Design Tool, provide noise estimates, yet they're unsuitable for individual addresses. HowLoud Inc.'s Soundscore, ranging from 50 to 100, overcomes this limitation. This proprietary index combines transportation noise models and local data to standardize noise measurement, aiding real estate and research. However, it's incomplete, missing scores for some areas, and several subject addresses did not have associated SoundScores.

This paper employs HowLoud's API to obtain and assess Soundscores for 63,363 addresses in Connecticut. We found that approximately 9% lacked Soundscores, especially in rural areas. Applying Tobler's First Law of Geography, which states that nearby values should be similar, we tested various interpolation methods to estimate these missing Soundscores. We found that Empirical Bayesian Kriging had the best results of these methods; however, it did not work for all locations. We then explored the relationship between these results and the subject's data.