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Background: Most epidemiological noise studies consider 24 h average noise exposure levels. Our aim was to exploratively analyze the impact of noise exposure at different time windows during day and night on cardiovascular mortality., Methods: We generated Switzerland-wide exposure models for road traffic, railway and aircraft noise for different time windows for the year 2001. Combined noise source equivalent continuous sound levels (L eq ) for different time windows at the most exposed façade were assigned to each of the 4.41 million Swiss National Cohort adult participants. Follow-up period was from 2000 to 2008. Hazard ratios (HR) of noise effects on various cardiovascular primary causes of death were computed by Cox regression models adjusted for potential confounders and NO 2 levels., Results: For most cardiovascular causes of death we obtained indications for a diurnal pattern. For ischemic heart disease the highest HR was observed for the core night hours from 01 h to 05 h (HR per standard deviation of L eq : 1.025, 95% CI: 1.016-1.034) and lower HR for the daytime 07 h to 19 h (1.018 [1.009-1.028]). Heart failure and daytime L eq yielded the highest HR (1.047 [1.027-1.068])., Conclusion: For acute cardiovascular diseases, nocturnal intermittent noise exposure tended to be more relevant than daytime exposure, whereas it was the opposite for chronic conditions such as heart failure most strongly associated with continuous daytime noise. This suggests that for acute diseases sleep is an important mediator for health consequences of transportation noise., (Copyright © 2018 Elsevier GmbH. All rights reserved.)

This article presents empirically derived conversion rules between the environmental noise exposure metrics Leq24h, LDay, LEvening, LNight, Ldn, and Lden for the noise sources road, rail and air traffic. It caters to researchers that need to estimate the value of one (unknown) noise metric from the value of another (known) metric, e.g. in the scope of epidemiological meta-analyses or systematic reviews, when results from different studies are pooled and need to be related to one common exposure metric. Conversion terms are derived using two empirical methods a) based on analyzing the diurnal variation of traffic, and b) by analyzing differences between calculated noise exposure metrics. For a) we collected and analyzed diurnal traffic share data from European and US airports as well as data on the diurnal variation of traffic from roads in several European countries and from railway lines in Switzerland which were derived from counting stations and official records. For b) we calculated differences between noise metrics in over 50'000 stratified randomly sampled dwellings in Switzerland. As a result of this exercise, conversion terms, including uncertainty estimates, are systematically tabulated for all variants of the target metrics. Guidance as to the practical applicability of the proposed conversions in different contexts is provided, and limitations of their use are discussed., (Copyright © 2017 Elsevier GmbH. All rights reserved.)