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      Associations between Aircraft Noise Exposure and Self-Reported Sleep Duration and Quality in the United States-Based Prospective Nurses’ Health Study Cohort

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          Abstract

          Background:

          Sleep disruption is linked with chronic disease, and aircraft noise can disrupt sleep. However, there are few investigations of aircraft noise and sleep in large cohorts.

          Objectives:

          We examined associations between aircraft noise and self-reported sleep duration and quality in the Nurses’ Health Study, a large prospective cohort.

          Methods:

          Aircraft nighttime equivalent sound levels (Lnight) and day–night average sound levels (DNL) were modeled around 90 U.S. airports from 1995 to 2015 in 5-y intervals using the Aviation Environmental Design Tool and linked to geocoded participant residential addresses. Lnight exposure was dichotomized at the lowest modeled level of 45 A-weighted decibels [dB(A)] and at multiple cut points for DNL. Multiple categories of both metrics were compared with < 45 dB(A). Self-reported short sleep duration ( < 7 h/24-h day) was ascertained in 2000, 2002, 2008, 2012, and 2014, and poor sleep quality (frequent trouble falling/staying asleep) was ascertained in 2000. We analyzed repeated sleep duration measures using generalized estimating equations and sleep quality by conditional logistic regression. We adjusted for participant-level demographics, behaviors, comorbidities, and environmental exposures (greenness and light at night) and examined effect modification.

          Results:

          In 35,226 female nurses averaging 66.1 years of age at baseline, prevalence of short sleep duration and poor sleep quality were 29.6% and 13.1%, respectively. In multivariable models, exposure to Lnight 45 dB(A) was associated with 23% [95% confidence interval (CI): 7%, 40%] greater odds of short sleep duration but was not associated with poor sleep quality (9% lower odds; 95% CI: 30 % , 19%). Increasing categories of Lnight and DNL 45 dB(A) suggested an exposure–response relationship for short sleep duration. We observed higher magnitude associations among participants living in the West, near major cargo airports, and near water-adjacent airports and among those reporting no hearing loss.

          Discussion:

          Aircraft noise was associated with short sleep duration in female nurses, modified by individual and airport characteristics. https://doi.org/10.1289/EHP10959

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          Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies.

          Aims To assess the relationship between duration of sleep and morbidity and mortality from coronary heart disease (CHD), stroke, and total cardiovascular disease (CVD). Methods and results We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. Studies were included if they were prospective, follow-up >3 years, had duration of sleep at baseline, and incident cases of CHD, stroke, or CVD. Relative risks (RR) and 95% confidence interval (CI) were pooled using a random-effect model. Overall, 15 studies (24 cohort samples) included 474 684 male and female participants (follow-up 6.9-25 years), and 16 067 events (4169 for CHD, 3478 for stroke, and 8420 for total CVD). Sleep duration was assessed by questionnaire and incident cases through certification and event registers. Short duration of sleep was associated with a greater risk of developing or dying of CHD (RR 1.48, 95% CI 1.22-1.80, P < 0.0001), stroke (1.15, 1.00-1.31, P = 0.047), but not total CVD (1.03, 0.93-1.15, P = 0.52) with no evidence of publication bias (P = 0.95, P = 0.30, and P = 0.46, respectively). Long duration of sleep was also associated with a greater risk of CHD (1.38, 1.15-1.66, P = 0.0005), stroke (1.65, 1.45-1.87, P < 0.0001), and total CVD (1.41, 1.19-1.68, P < 0.0001) with no evidence of publication bias (P = 0.92, P = 0.96, and P = 0.79, respectively). Conclusion Both short and long duration of sleep are predictors, or markers, of cardiovascular outcomes.
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            Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

            Directed acyclic graphs (DAGs), which offer systematic representations of causal relationships, have become an established framework for the analysis of causal inference in epidemiology, often being used to determine covariate adjustment sets for minimizing confounding bias. DAGitty is a popular web application for drawing and analysing DAGs. Here we introduce the R package 'dagitty', which provides access to all of the capabilities of the DAGitty web application within the R platform for statistical computing, and also offers several new functions. We describe how the R package 'dagitty' can be used to: evaluate whether a DAG is consistent with the dataset it is intended to represent; enumerate 'statistically equivalent' but causally different DAGs; and identify exposure-outcome adjustment sets that are valid for causally different but statistically equivalent DAGs. This functionality enables epidemiologists to detect causal misspecifications in DAGs and make robust inferences that remain valid for a range of different DAGs. The R package 'dagitty' is available through the comprehensive R archive network (CRAN) at [https://cran.r-project.org/web/packages/dagitty/]. The source code is available on github at [https://github.com/jtextor/dagitty]. The web application 'DAGitty' is free software, licensed under the GNU general public licence (GPL) version 2 and is available at [http://dagitty.net/].
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              Is Open Access

              Quantity and Quality of Sleep and Incidence of Type 2 Diabetes

              OBJECTIVE To assess the relationship between habitual sleep disturbances and the incidence of type 2 diabetes and to obtain an estimate of the risk. RESEARCH DESIGN AND METHODS We conducted a systematic search of publications using MEDLINE (1955–April 2009), EMBASE, and the Cochrane Library and manual searches without language restrictions. We included studies if they were prospective with follow-up >3 years and had an assessment of sleep disturbances at baseline and incidence of type 2 diabetes. We recorded several characteristics for each study. We extracted quantity and quality of sleep, how they were assessed, and incident cases defined with different validated methods. We extracted relative risks (RRs) and 95% CI and pooled them using random-effects models. We performed sensitivity analysis and assessed heterogeneity and publication bias. RESULTS We included 10 studies (13 independent cohort samples; 107,756 male and female participants, follow-up range 4.2–32 years, and 3,586 incident cases of type 2 diabetes). In pooled analyses, quantity and quality of sleep predicted the risk of development of type 2 diabetes. For short duration of sleep (≤5–6 h/night), the RR was 1.28 (95% CI 1.03–1.60, P = 0.024, heterogeneity P = 0.015); for long duration of sleep (>8–9 h/night), the RR was 1.48 (1.13–1.96, P = 0.005); for difficulty in initiating sleep, the RR was 1.57 (1.25–1.97, P < 0.0001); and for difficulty in maintaining sleep, the RR was 1.84 (1.39–2.43, P < 0.0001). CONCLUSIONS Quantity and quality of sleep consistently and significantly predict the risk of the development of type 2 diabetes. The mechanisms underlying this relation may differ between short and long sleepers.
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                Author and article information

                Journal
                Environ Health Perspect
                Environ Health Perspect
                EHP
                Environmental Health Perspectives
                Environmental Health Perspectives
                0091-6765
                1552-9924
                14 April 2023
                April 2023
                : 131
                : 4
                : 047010
                Affiliations
                [ 1 ]Department of Environmental Health, Boston University School of Public Health , Boston, Massachusetts, USA
                [ 2 ]Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School , Boston, Massachusetts, USA
                [ 3 ]Department of Epidemiology, Harvard T.H. Chan School of Public Health , Boston, Massachusetts, USA
                [ 4 ]Beth Israel Deaconess Medical Center , Boston, Massachusetts, USA
                [ 5 ]Department of Environmental Health, Harvard T.H. Chan School of Public Health , Boston, Massachusetts, USA
                [ 6 ]Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute , Boston, Massachusetts, USA
                [ 7 ]Volpe National Transportation Systems Center, U.S. Department of Transportation , Cambridge, Massachusetts, USA
                Author notes
                Address correspondence to Matthew Bozigar, 160 SW 26th St., Corvallis, OR 97331 USA. Email: bozigarm@ 123456oregonstate.edu
                Author information
                https://orcid.org/0000-0003-0429-0247
                https://orcid.org/0000-0001-8420-9167
                https://orcid.org/0000-0002-0826-1163
                https://orcid.org/0000-0002-1544-358X
                https://orcid.org/0000-0001-6748-4677
                https://orcid.org/0000-0002-2858-1973
                https://orcid.org/0000-0002-6929-4305
                https://orcid.org/0000-0002-1116-4006
                https://orcid.org/0000-0002-2813-2174
                https://orcid.org/0000-0003-4542-4563
                Article
                EHP10959
                10.1289/EHP10959
                10104165
                37058435
                f96c1c2e-1e0c-4da5-9719-61e62bdda0e1

                EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.

                History
                : 17 January 2022
                : 21 February 2023
                : 03 March 2023
                Categories
                Research

                Public health
                Public health

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