Evidence map›Paper›PMID 40684001›Full record

ArticleJournal of exposure science & environmental epidemiology2026

Systematic measurement and machine learning-based profile characterization of community noise in a medium-large city in the United States.

Carson Mowrer, Andrew Larkin, Charlotte Roscoe, Stephanie T Grady, Junenette L Peters, Brendon Haggerty, Perry Hystad, Matthew Bozigar

Abstract read
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In one paragraph

Article in Journal of exposure science & environmental epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Carson MowrerSchool of Nutrition and Public Health, College of Health, Oregon State University, Corvallis, OR, USA. mowrerc@oregonstate.edu.ORCID http://orcid.org/0009-0002-0651-833X
Andrew LarkinSchool of Nutrition and Public Health, College of Health, Oregon State University, Corvallis, OR, USA.
Charlotte RoscoeOregon Health and Science University-Portland State University School of Public Health, Portland, OR, USA.
Stephanie T GradyDepartment of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
Junenette L PetersDepartment of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
Brendon HaggertyHealthy Homes and Communities Program, Multnomah County Health Department, Portland, OR, USA.
Perry HystadSchool of Nutrition and Public Health, College of Health, Oregon State University, Corvallis, OR, USA.
Matthew BozigarSchool of Nutrition and Public Health, College of Health, Oregon State University, Corvallis, OR, USA. matthew.bozigar@oregonstate.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommunity noise pollution can adversely impact health, yet noise has rarely been systematically measured in United States (U.S.) cities for epidemiological research.

objectiveCollaborating with the Multnomah County Health Department, we developed an exploratory measurement campaign to systematically capture community noise in Portland, Oregon, U.S. to inform environmental health research and practice.

methodsWe identified short-term measurement locations using weighted probability sampling and developed a protocol for deploying Class 1 sound level meters at identified sites to measure sound levels continuously for at least five days. We calculated daytime, nighttime, and daily-average noise metrics including day-night average sound levels (DNL), day-evening-night levels (L

resultsDNL ranged from 49.6 to 86.7 decibels across short-term sites (n = 217). DNL exceeded U.S. Environmental Protection Agency guidelines at 78% of sites, and nighttime noise exceeded World Health Organization guidelines at 90%. Short-term sites in census tracts with higher median income and proportion of white population had lower DNL compared to lower median income and proportion of white population census tracts. Cluster analysis revealed four noise profiles: low LA IMPACT: This study reveals a high prevalence of potentially harmful community noise exposure levels in a medium-large city in the United States, particularly in lower-income and racially diverse neighborhoods. By identifying groupings of sites with similar noise exposure profiles, we establish a foundation for exploring built environment drivers of noise and differential health impacts of multidimensional noise exposures. The measurement protocol and database of noise measurements collected provides tools for researchers and communities (available upon request) to investigate noise exposure patterns, environmental justice concerns, and associated health impacts, with further applications for predictive modeling to estimate individual-level exposures in epidemiologic studies.

Indexed as

Environmental ExposureEnvironmental MonitoringMachine LearningNoiseBuilt EnvironmentCitiesHumansOregonUnited StatesEnvironmental justiceEnvironmental noiseIntermittency ratioNoise assessmentRoad traffic noise

Identifiers

PMID40684001

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.