Depressive symptoms of people living in areas with high exposure to environmental noise: a multilevel analysis Article Swipe
Il Yun
,
Seung‐Hwan Lee
,
Sohee Park
,
Suk‐Yong Jang
,
Sung‐In Jang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-3492597/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-3492597/v1
BackgroundExposure and damage caused by noise have been reported in many countries around the world. However, few nationwide studies explored the association of residential environmental noise with depressive symptoms, this study aims to examine this association.MethodsThe Korean Community Health Survey at the individual-level and the Korean Environmental Noise Measurement Database at the regional-level were used. A total of 30,630 individuals were eligible for the analysis. Multilevel model framework was applied to account for the clustered structure of the regional-level data in which individual-level data containing demographic characteristics and health information were nested.ResultsIndividuals living in the highest environmental noise area had a 1.55 times higher likelihood of experiencing depressive symptoms than those living in the lowest environmental noise area (95% CI, 1.04−2.31). After stratified analysis according to depressive symptom severity, individuals residing in areas with the highest environmental noise exposure had significantly higher odds of mild (aOR, 1.46; 95% CI, 1.02−2.07) and moderate symptoms (aOR, 1.70; 95% CI, 1.00−2.91).LimitationsBecause secondary data were used, time series analysis to track changes in outcomes was not possible. The PHQ-9 questionnaires, which measures depressive symptoms, were self-reported. Due to the absence of data on inter-floor noise, it could not include in the analysis. Residual confounders from unmeasured variables could not be ruled out.ConclusionsThe higher the residential environmental noise, the higher the possibility of mild-to-moderate depressive symptoms. Our findings suggest the need for continued attention to and management of noise pollution, which has the potential to adversely affect individual's mental health.
Related Topics
Concepts
Environmental noise
Confounding
Multilevel model
Noise (video)
Odds
Environmental health
Depressive symptoms
Odds ratio
Medicine
Demography
Psychology
Logistic regression
Statistics
Psychiatry
Cognition
Mathematics
Computer science
Pathology
Geology
Artificial intelligence
Sociology
Geomorphology
Sound (geography)
Image (mathematics)
Internal medicine
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-3492597/v1
- https://www.researchsquare.com/article/rs-3492597/latest.pdf
- OA Status
- gold
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388128189
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4388128189Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-3492597/v1Digital Object Identifier
- Title
-
Depressive symptoms of people living in areas with high exposure to environmental noise: a multilevel analysisWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-11-01Full publication date if available
- Authors
-
Il Yun, Seung‐Hwan Lee, Sohee Park, Suk‐Yong Jang, Sung‐In JangList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-3492597/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-3492597/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-3492597/latest.pdfDirect OA link when available
- Concepts
-
Environmental noise, Confounding, Multilevel model, Noise (video), Odds, Environmental health, Depressive symptoms, Odds ratio, Medicine, Demography, Psychology, Logistic regression, Statistics, Psychiatry, Cognition, Mathematics, Computer science, Pathology, Geology, Artificial intelligence, Sociology, Geomorphology, Sound (geography), Image (mathematics), Internal medicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
27Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4388128189 |
|---|---|
| doi | https://doi.org/10.21203/rs.3.rs-3492597/v1 |
| ids.doi | https://doi.org/10.21203/rs.3.rs-3492597/v1 |
| ids.openalex | https://openalex.org/W4388128189 |
| fwci | 0.0 |
| type | preprint |
| title | Depressive symptoms of people living in areas with high exposure to environmental noise: a multilevel analysis |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11692 |
| topics[0].field.id | https://openalex.org/fields/36 |
| topics[0].field.display_name | Health Professions |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3616 |
| topics[0].subfield.display_name | Speech and Hearing |
| topics[0].display_name | Noise Effects and Management |
| topics[1].id | https://openalex.org/T10283 |
| topics[1].field.id | https://openalex.org/fields/28 |
| topics[1].field.display_name | Neuroscience |
| topics[1].score | 0.9883999824523926 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2805 |
| topics[1].subfield.display_name | Cognitive Neuroscience |
| topics[1].display_name | Hearing Loss and Rehabilitation |
| topics[2].id | https://openalex.org/T10822 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9854999780654907 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2204 |
| topics[2].subfield.display_name | Biomedical Engineering |
| topics[2].display_name | Acoustic Wave Phenomena Research |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C86781634 |
| concepts[0].level | 3 |
| concepts[0].score | 0.6283109784126282 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q2478325 |
| concepts[0].display_name | Environmental noise |
| concepts[1].id | https://openalex.org/C77350462 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6091159582138062 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1125472 |
| concepts[1].display_name | Confounding |
| concepts[2].id | https://openalex.org/C53059260 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5903193950653076 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q374758 |
| concepts[2].display_name | Multilevel model |
| concepts[3].id | https://openalex.org/C99498987 |
| concepts[3].level | 3 |
| concepts[3].score | 0.5407353639602661 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2210247 |
| concepts[3].display_name | Noise (video) |
| concepts[4].id | https://openalex.org/C143095724 |
| concepts[4].level | 3 |
| concepts[4].score | 0.5002458095550537 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q515895 |
| concepts[4].display_name | Odds |
| concepts[5].id | https://openalex.org/C99454951 |
| concepts[5].level | 1 |
| concepts[5].score | 0.49433279037475586 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q932068 |
| concepts[5].display_name | Environmental health |
| concepts[6].id | https://openalex.org/C3019858935 |
| concepts[6].level | 3 |
| concepts[6].score | 0.4583105742931366 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q4340209 |
| concepts[6].display_name | Depressive symptoms |
| concepts[7].id | https://openalex.org/C156957248 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4567367732524872 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1862216 |
| concepts[7].display_name | Odds ratio |
| concepts[8].id | https://openalex.org/C71924100 |
| concepts[8].level | 0 |
| concepts[8].score | 0.4485520124435425 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[8].display_name | Medicine |
| concepts[9].id | https://openalex.org/C149923435 |
| concepts[9].level | 1 |
| concepts[9].score | 0.41376304626464844 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q37732 |
| concepts[9].display_name | Demography |
| concepts[10].id | https://openalex.org/C15744967 |
| concepts[10].level | 0 |
| concepts[10].score | 0.3455834984779358 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[10].display_name | Psychology |
| concepts[11].id | https://openalex.org/C151956035 |
| concepts[11].level | 2 |
| concepts[11].score | 0.23647162318229675 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1132755 |
| concepts[11].display_name | Logistic regression |
| concepts[12].id | https://openalex.org/C105795698 |
| concepts[12].level | 1 |
| concepts[12].score | 0.17749419808387756 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[12].display_name | Statistics |
| concepts[13].id | https://openalex.org/C118552586 |
| concepts[13].level | 1 |
| concepts[13].score | 0.1097971498966217 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7867 |
| concepts[13].display_name | Psychiatry |
| concepts[14].id | https://openalex.org/C169900460 |
| concepts[14].level | 2 |
| concepts[14].score | 0.07808703184127808 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q2200417 |
| concepts[14].display_name | Cognition |
| concepts[15].id | https://openalex.org/C33923547 |
| concepts[15].level | 0 |
| concepts[15].score | 0.07550233602523804 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[15].display_name | Mathematics |
| concepts[16].id | https://openalex.org/C41008148 |
| concepts[16].level | 0 |
| concepts[16].score | 0.07257306575775146 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[16].display_name | Computer science |
| concepts[17].id | https://openalex.org/C142724271 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7208 |
| concepts[17].display_name | Pathology |
| concepts[18].id | https://openalex.org/C127313418 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[18].display_name | Geology |
| concepts[19].id | https://openalex.org/C154945302 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[19].display_name | Artificial intelligence |
| concepts[20].id | https://openalex.org/C144024400 |
| concepts[20].level | 0 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q21201 |
| concepts[20].display_name | Sociology |
| concepts[21].id | https://openalex.org/C114793014 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q52109 |
| concepts[21].display_name | Geomorphology |
| concepts[22].id | https://openalex.org/C203718221 |
| concepts[22].level | 2 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q491713 |
| concepts[22].display_name | Sound (geography) |
| concepts[23].id | https://openalex.org/C115961682 |
| concepts[23].level | 2 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[23].display_name | Image (mathematics) |
| concepts[24].id | https://openalex.org/C126322002 |
| concepts[24].level | 1 |
| concepts[24].score | 0.0 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q11180 |
| concepts[24].display_name | Internal medicine |
| keywords[0].id | https://openalex.org/keywords/environmental-noise |
| keywords[0].score | 0.6283109784126282 |
| keywords[0].display_name | Environmental noise |
| keywords[1].id | https://openalex.org/keywords/confounding |
| keywords[1].score | 0.6091159582138062 |
| keywords[1].display_name | Confounding |
| keywords[2].id | https://openalex.org/keywords/multilevel-model |
| keywords[2].score | 0.5903193950653076 |
| keywords[2].display_name | Multilevel model |
| keywords[3].id | https://openalex.org/keywords/noise |
| keywords[3].score | 0.5407353639602661 |
| keywords[3].display_name | Noise (video) |
| keywords[4].id | https://openalex.org/keywords/odds |
| keywords[4].score | 0.5002458095550537 |
| keywords[4].display_name | Odds |
| keywords[5].id | https://openalex.org/keywords/environmental-health |
| keywords[5].score | 0.49433279037475586 |
| keywords[5].display_name | Environmental health |
| keywords[6].id | https://openalex.org/keywords/depressive-symptoms |
| keywords[6].score | 0.4583105742931366 |
| keywords[6].display_name | Depressive symptoms |
| keywords[7].id | https://openalex.org/keywords/odds-ratio |
| keywords[7].score | 0.4567367732524872 |
| keywords[7].display_name | Odds ratio |
| keywords[8].id | https://openalex.org/keywords/medicine |
| keywords[8].score | 0.4485520124435425 |
| keywords[8].display_name | Medicine |
| keywords[9].id | https://openalex.org/keywords/demography |
| keywords[9].score | 0.41376304626464844 |
| keywords[9].display_name | Demography |
| keywords[10].id | https://openalex.org/keywords/psychology |
| keywords[10].score | 0.3455834984779358 |
| keywords[10].display_name | Psychology |
| keywords[11].id | https://openalex.org/keywords/logistic-regression |
| keywords[11].score | 0.23647162318229675 |
| keywords[11].display_name | Logistic regression |
| keywords[12].id | https://openalex.org/keywords/statistics |
| keywords[12].score | 0.17749419808387756 |
| keywords[12].display_name | Statistics |
| keywords[13].id | https://openalex.org/keywords/psychiatry |
| keywords[13].score | 0.1097971498966217 |
| keywords[13].display_name | Psychiatry |
| keywords[14].id | https://openalex.org/keywords/cognition |
| keywords[14].score | 0.07808703184127808 |
| keywords[14].display_name | Cognition |
| keywords[15].id | https://openalex.org/keywords/mathematics |
| keywords[15].score | 0.07550233602523804 |
| keywords[15].display_name | Mathematics |
| keywords[16].id | https://openalex.org/keywords/computer-science |
| keywords[16].score | 0.07257306575775146 |
| keywords[16].display_name | Computer science |
| language | en |
| locations[0].id | doi:10.21203/rs.3.rs-3492597/v1 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.researchsquare.com/article/rs-3492597/latest.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.21203/rs.3.rs-3492597/v1 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5061463295 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-9187-4456 |
| authorships[0].author.display_name | Il Yun |
| authorships[0].countries | KR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210097774 |
| authorships[0].affiliations[0].raw_affiliation_string | Korea Health Industry Development Institute Sohee Park |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I193775966 |
| authorships[0].affiliations[1].raw_affiliation_string | Yonsei University |
| authorships[0].affiliations[2].institution_ids | https://openalex.org/I193775966 |
| authorships[0].affiliations[2].raw_affiliation_string | Yonsei University College of Medicine |
| authorships[0].institutions[0].id | https://openalex.org/I4210097774 |
| authorships[0].institutions[0].ror | https://ror.org/00fdzyk40 |
| authorships[0].institutions[0].type | government |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210097774 |
| authorships[0].institutions[0].country_code | KR |
| authorships[0].institutions[0].display_name | Korea Health Industry Development Institute |
| authorships[0].institutions[1].id | https://openalex.org/I193775966 |
| authorships[0].institutions[1].ror | https://ror.org/01wjejq96 |
| authorships[0].institutions[1].type | education |
| authorships[0].institutions[1].lineage | https://openalex.org/I193775966 |
| authorships[0].institutions[1].country_code | KR |
| authorships[0].institutions[1].display_name | Yonsei University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Il Yun |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Korea Health Industry Development Institute Sohee Park, Yonsei University, Yonsei University College of Medicine |
| authorships[1].author.id | https://openalex.org/A5100410174 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-3964-3877 |
| authorships[1].author.display_name | Seung‐Hwan Lee |
| authorships[1].countries | KR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I193775966 |
| authorships[1].affiliations[0].raw_affiliation_string | Yonsei University College of Medicine |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I4210097774 |
| authorships[1].affiliations[1].raw_affiliation_string | Korea Health Industry Development Institute Sohee Park |
| authorships[1].affiliations[2].institution_ids | https://openalex.org/I193775966 |
| authorships[1].affiliations[2].raw_affiliation_string | Yonsei University |
| authorships[1].institutions[0].id | https://openalex.org/I4210097774 |
| authorships[1].institutions[0].ror | https://ror.org/00fdzyk40 |
| authorships[1].institutions[0].type | government |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210097774 |
| authorships[1].institutions[0].country_code | KR |
| authorships[1].institutions[0].display_name | Korea Health Industry Development Institute |
| authorships[1].institutions[1].id | https://openalex.org/I193775966 |
| authorships[1].institutions[1].ror | https://ror.org/01wjejq96 |
| authorships[1].institutions[1].type | education |
| authorships[1].institutions[1].lineage | https://openalex.org/I193775966 |
| authorships[1].institutions[1].country_code | KR |
| authorships[1].institutions[1].display_name | Yonsei University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Seung Hwan Lee |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Korea Health Industry Development Institute Sohee Park, Yonsei University, Yonsei University College of Medicine |
| authorships[2].author.id | https://openalex.org/A5100739374 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-8513-5163 |
| authorships[2].author.display_name | Sohee Park |
| authorships[2].countries | KR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I193775966 |
| authorships[2].affiliations[0].raw_affiliation_string | Yonsei University |
| authorships[2].institutions[0].id | https://openalex.org/I193775966 |
| authorships[2].institutions[0].ror | https://ror.org/01wjejq96 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I193775966 |
| authorships[2].institutions[0].country_code | KR |
| authorships[2].institutions[0].display_name | Yonsei University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sohee Park |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Yonsei University |
| authorships[3].author.id | https://openalex.org/A5062430204 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-0558-1505 |
| authorships[3].author.display_name | Suk‐Yong Jang |
| authorships[3].countries | KR |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I193775966 |
| authorships[3].affiliations[0].raw_affiliation_string | Yonsei University College of Medicine |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I4210097774 |
| authorships[3].affiliations[1].raw_affiliation_string | Korea Health Industry Development Institute Sohee Park |
| authorships[3].affiliations[2].institution_ids | https://openalex.org/I193775966 |
| authorships[3].affiliations[2].raw_affiliation_string | Yonsei University |
| authorships[3].institutions[0].id | https://openalex.org/I4210097774 |
| authorships[3].institutions[0].ror | https://ror.org/00fdzyk40 |
| authorships[3].institutions[0].type | government |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210097774 |
| authorships[3].institutions[0].country_code | KR |
| authorships[3].institutions[0].display_name | Korea Health Industry Development Institute |
| authorships[3].institutions[1].id | https://openalex.org/I193775966 |
| authorships[3].institutions[1].ror | https://ror.org/01wjejq96 |
| authorships[3].institutions[1].type | education |
| authorships[3].institutions[1].lineage | https://openalex.org/I193775966 |
| authorships[3].institutions[1].country_code | KR |
| authorships[3].institutions[1].display_name | Yonsei University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Suk-yong Jang |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | Korea Health Industry Development Institute Sohee Park, Yonsei University, Yonsei University College of Medicine |
| authorships[4].author.id | https://openalex.org/A5003289938 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-0760-2878 |
| authorships[4].author.display_name | Sung‐In Jang |
| authorships[4].countries | KR |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I193775966 |
| authorships[4].affiliations[0].raw_affiliation_string | Yonsei University College of Medicine |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I193775966 |
| authorships[4].affiliations[1].raw_affiliation_string | Yonsei University |
| authorships[4].affiliations[2].institution_ids | https://openalex.org/I4210097774 |
| authorships[4].affiliations[2].raw_affiliation_string | Korea Health Industry Development Institute Sohee Park |
| authorships[4].institutions[0].id | https://openalex.org/I4210097774 |
| authorships[4].institutions[0].ror | https://ror.org/00fdzyk40 |
| authorships[4].institutions[0].type | government |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210097774 |
| authorships[4].institutions[0].country_code | KR |
| authorships[4].institutions[0].display_name | Korea Health Industry Development Institute |
| authorships[4].institutions[1].id | https://openalex.org/I193775966 |
| authorships[4].institutions[1].ror | https://ror.org/01wjejq96 |
| authorships[4].institutions[1].type | education |
| authorships[4].institutions[1].lineage | https://openalex.org/I193775966 |
| authorships[4].institutions[1].country_code | KR |
| authorships[4].institutions[1].display_name | Yonsei University |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Sung-In Jang |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Korea Health Industry Development Institute Sohee Park, Yonsei University, Yonsei University College of Medicine |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.researchsquare.com/article/rs-3492597/latest.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Depressive symptoms of people living in areas with high exposure to environmental noise: a multilevel analysis |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11692 |
| primary_topic.field.id | https://openalex.org/fields/36 |
| primary_topic.field.display_name | Health Professions |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3616 |
| primary_topic.subfield.display_name | Speech and Hearing |
| primary_topic.display_name | Noise Effects and Management |
| related_works | https://openalex.org/W1604849300, https://openalex.org/W2766061861, https://openalex.org/W1604293003, https://openalex.org/W2994176440, https://openalex.org/W1979850356, https://openalex.org/W3005040438, https://openalex.org/W2481749367, https://openalex.org/W1520846789, https://openalex.org/W3124750890, https://openalex.org/W3186119517 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.21203/rs.3.rs-3492597/v1 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.researchsquare.com/article/rs-3492597/latest.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.21203/rs.3.rs-3492597/v1 |
| primary_location.id | doi:10.21203/rs.3.rs-3492597/v1 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.researchsquare.com/article/rs-3492597/latest.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.21203/rs.3.rs-3492597/v1 |
| publication_date | 2023-11-01 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2063634210, https://openalex.org/W2560611641, https://openalex.org/W4290086754, https://openalex.org/W2953743685, https://openalex.org/W2111114823, https://openalex.org/W4403732152, https://openalex.org/W2102936404, https://openalex.org/W3018996869, https://openalex.org/W2895891833, https://openalex.org/W2014192294, https://openalex.org/W2170834074, https://openalex.org/W3120577633, https://openalex.org/W4200006969, https://openalex.org/W2753590254, https://openalex.org/W2034242390, https://openalex.org/W2061521761, https://openalex.org/W3132151938, https://openalex.org/W2327942635, https://openalex.org/W2345741677, https://openalex.org/W4310249198, https://openalex.org/W2791491088, https://openalex.org/W4296797132, https://openalex.org/W2026822459, https://openalex.org/W2010676081, https://openalex.org/W2016579647, https://openalex.org/W2954581064, https://openalex.org/W2261625734 |
| referenced_works_count | 27 |
| abstract_inverted_index.A | 56 |
| abstract_inverted_index.a | 101 |
| abstract_inverted_index.at | 41, 51 |
| abstract_inverted_index.be | 206 |
| abstract_inverted_index.by | 5 |
| abstract_inverted_index.in | 10, 81, 94, 113, 132, 169, 196 |
| abstract_inverted_index.it | 192 |
| abstract_inverted_index.of | 23, 58, 77, 106, 144, 187, 218, 233 |
| abstract_inverted_index.on | 189 |
| abstract_inverted_index.to | 33, 71, 126, 166, 184, 230, 240 |
| abstract_inverted_index.95% | 148, 156 |
| abstract_inverted_index.CI, | 120, 149, 157 |
| abstract_inverted_index.Due | 183 |
| abstract_inverted_index.Our | 222 |
| abstract_inverted_index.The | 174 |
| abstract_inverted_index.and | 2, 44, 88, 151, 231 |
| abstract_inverted_index.few | 17 |
| abstract_inverted_index.for | 63, 73, 227 |
| abstract_inverted_index.had | 100, 140 |
| abstract_inverted_index.has | 237 |
| abstract_inverted_index.not | 172, 194, 205 |
| abstract_inverted_index.the | 14, 21, 42, 45, 52, 64, 74, 78, 95, 114, 135, 185, 197, 210, 214, 216, 225, 238 |
| abstract_inverted_index.was | 69, 171 |
| abstract_inverted_index.(95% | 119 |
| abstract_inverted_index.1.55 | 102 |
| abstract_inverted_index.aims | 32 |
| abstract_inverted_index.area | 99, 118 |
| abstract_inverted_index.been | 8 |
| abstract_inverted_index.data | 80, 84, 160, 188 |
| abstract_inverted_index.from | 201 |
| abstract_inverted_index.have | 7 |
| abstract_inverted_index.many | 11 |
| abstract_inverted_index.mild | 145 |
| abstract_inverted_index.need | 226 |
| abstract_inverted_index.odds | 143 |
| abstract_inverted_index.than | 110 |
| abstract_inverted_index.this | 30, 35 |
| abstract_inverted_index.time | 163 |
| abstract_inverted_index.were | 54, 61, 91, 161, 181 |
| abstract_inverted_index.with | 27, 134 |
| abstract_inverted_index.(aOR, | 146, 154 |
| abstract_inverted_index.1.46; | 147 |
| abstract_inverted_index.1.70; | 155 |
| abstract_inverted_index.After | 122 |
| abstract_inverted_index.Noise | 48 |
| abstract_inverted_index.PHQ-9 | 175 |
| abstract_inverted_index.areas | 133 |
| abstract_inverted_index.could | 193, 204 |
| abstract_inverted_index.model | 67 |
| abstract_inverted_index.noise | 6, 26, 98, 117, 138, 234 |
| abstract_inverted_index.ruled | 207 |
| abstract_inverted_index.study | 31 |
| abstract_inverted_index.those | 111 |
| abstract_inverted_index.times | 103 |
| abstract_inverted_index.total | 57 |
| abstract_inverted_index.track | 167 |
| abstract_inverted_index.used, | 162 |
| abstract_inverted_index.used. | 55 |
| abstract_inverted_index.which | 82, 177, 236 |
| abstract_inverted_index.30,630 | 59 |
| abstract_inverted_index.Health | 39 |
| abstract_inverted_index.Korean | 37, 46 |
| abstract_inverted_index.Survey | 40 |
| abstract_inverted_index.affect | 242 |
| abstract_inverted_index.around | 13 |
| abstract_inverted_index.caused | 4 |
| abstract_inverted_index.damage | 3 |
| abstract_inverted_index.health | 89 |
| abstract_inverted_index.higher | 104, 142, 209, 215 |
| abstract_inverted_index.living | 93, 112 |
| abstract_inverted_index.lowest | 115 |
| abstract_inverted_index.mental | 244 |
| abstract_inverted_index.noise, | 191, 213 |
| abstract_inverted_index.series | 164 |
| abstract_inverted_index.world. | 15 |
| abstract_inverted_index.absence | 186 |
| abstract_inverted_index.account | 72 |
| abstract_inverted_index.applied | 70 |
| abstract_inverted_index.changes | 168 |
| abstract_inverted_index.examine | 34 |
| abstract_inverted_index.health. | 245 |
| abstract_inverted_index.highest | 96, 136 |
| abstract_inverted_index.include | 195 |
| abstract_inverted_index.studies | 19 |
| abstract_inverted_index.suggest | 224 |
| abstract_inverted_index.symptom | 128 |
| abstract_inverted_index.Database | 50 |
| abstract_inverted_index.However, | 16 |
| abstract_inverted_index.Residual | 199 |
| abstract_inverted_index.analysis | 124, 165 |
| abstract_inverted_index.eligible | 62 |
| abstract_inverted_index.explored | 20 |
| abstract_inverted_index.exposure | 139 |
| abstract_inverted_index.findings | 223 |
| abstract_inverted_index.measures | 178 |
| abstract_inverted_index.moderate | 152 |
| abstract_inverted_index.outcomes | 170 |
| abstract_inverted_index.reported | 9 |
| abstract_inverted_index.residing | 131 |
| abstract_inverted_index.symptoms | 109, 153 |
| abstract_inverted_index.Community | 38 |
| abstract_inverted_index.according | 125 |
| abstract_inverted_index.adversely | 241 |
| abstract_inverted_index.analysis. | 65, 198 |
| abstract_inverted_index.attention | 229 |
| abstract_inverted_index.clustered | 75 |
| abstract_inverted_index.continued | 228 |
| abstract_inverted_index.countries | 12 |
| abstract_inverted_index.framework | 68 |
| abstract_inverted_index.possible. | 173 |
| abstract_inverted_index.potential | 239 |
| abstract_inverted_index.secondary | 159 |
| abstract_inverted_index.severity, | 129 |
| abstract_inverted_index.structure | 76 |
| abstract_inverted_index.symptoms, | 29, 180 |
| abstract_inverted_index.symptoms. | 221 |
| abstract_inverted_index.variables | 203 |
| abstract_inverted_index.Multilevel | 66 |
| abstract_inverted_index.containing | 85 |
| abstract_inverted_index.depressive | 28, 108, 127, 179, 220 |
| abstract_inverted_index.likelihood | 105 |
| abstract_inverted_index.management | 232 |
| abstract_inverted_index.nationwide | 18 |
| abstract_inverted_index.pollution, | 235 |
| abstract_inverted_index.stratified | 123 |
| abstract_inverted_index.unmeasured | 202 |
| abstract_inverted_index.Measurement | 49 |
| abstract_inverted_index.association | 22 |
| abstract_inverted_index.confounders | 200 |
| abstract_inverted_index.demographic | 86 |
| abstract_inverted_index.individuals | 60, 130 |
| abstract_inverted_index.information | 90 |
| abstract_inverted_index.inter-floor | 190 |
| abstract_inverted_index.possibility | 217 |
| abstract_inverted_index.residential | 24, 211 |
| abstract_inverted_index.1.02−2.07) | 150 |
| abstract_inverted_index.experiencing | 107 |
| abstract_inverted_index.individual's | 243 |
| abstract_inverted_index.1.04−2.31). | 121 |
| abstract_inverted_index.Environmental | 47 |
| abstract_inverted_index.environmental | 25, 97, 116, 137, 212 |
| abstract_inverted_index.significantly | 141 |
| abstract_inverted_index.regional-level | 53, 79 |
| abstract_inverted_index.self-reported. | 182 |
| abstract_inverted_index.characteristics | 87 |
| abstract_inverted_index.questionnaires, | 176 |
| abstract_inverted_index.individual-level | 43, 83 |
| abstract_inverted_index.mild-to-moderate | 219 |
| abstract_inverted_index.<title>Abstract</title> | 0 |
| abstract_inverted_index.<bold>Background</bold>Exposure | 1 |
| abstract_inverted_index.out.<bold>Conclusions</bold>The | 208 |
| abstract_inverted_index.association.<bold>Methods</bold>The | 36 |
| abstract_inverted_index.nested.<bold>Results</bold>Individuals | 92 |
| abstract_inverted_index.1.00−2.91).<bold>Limitations</bold>Because | 158 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5062430204 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I193775966, https://openalex.org/I4210097774 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.4000000059604645 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.26608207 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |