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Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults
BACKGROUND: Depression and anxiety are top contributors to non-fatal health loss globally. Several studies have indicated the association between residential greenness and mental health. METHOD: The participants (n = 27,366) were recruited from four counties in Henan Province, China during 2015–2017...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454668/ https://www.ncbi.nlm.nih.gov/pubmed/34557719 http://dx.doi.org/10.1016/j.xinn.2020.100054 |
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author | Di, Niu Li, Shanshan Xiang, Hao Xie, Yinyu Mao, Zhenxing Hou, Jian Liu, Xiaotian Huo, Wenqian Yang, Boyi Dong, Guanghui Wang, Chongjian Chen, Gongbo Guo, Yuming |
author_facet | Di, Niu Li, Shanshan Xiang, Hao Xie, Yinyu Mao, Zhenxing Hou, Jian Liu, Xiaotian Huo, Wenqian Yang, Boyi Dong, Guanghui Wang, Chongjian Chen, Gongbo Guo, Yuming |
author_sort | Di, Niu |
collection | PubMed |
description | BACKGROUND: Depression and anxiety are top contributors to non-fatal health loss globally. Several studies have indicated the association between residential greenness and mental health. METHOD: The participants (n = 27,366) were recruited from four counties in Henan Province, China during 2015–2017. Symptoms of depression and anxiety were evaluated using the Patient Health Questionnaire-2 (PHQ-2) and the Generalized Anxiety Disorder-2 (GAD-2) in the baseline survey. The level of residential greenness during the 3-year period before the baseline survey was assessed using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The mixed-effect linear regression model was applied to examine the associations of residential greenness with depression and anxiety. RESULTS: The results of adjusted models showed that the score of PHQ-2 (Δscore and 95% confidence interval [CI]) decreased by −0.024 (−0.041, −0.006) and −0.022 (−0.038, −0.004) with an interquartile range (IQR) increase in NDVI and EVI within a 1,000-m buffer radius, respectively. The score of GAD-2 (Δscore and 95% CI) decreased by −0.024 (−0.040, −0.006) and −0.028 (−0.044, −0.011), in relation to an IQR increase in NDVI and EVI within a 1,000-m buffer radius, respectively. CONCLUSIONS: A higher level of residential greenness was significantly associated with lower risk of depression and anxiety in rural areas of Henan Province. Improving residential greenness accessibility may help to promote the mental health of rural populations. |
format | Online Article Text |
id | pubmed-8454668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-84546682021-09-22 Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults Di, Niu Li, Shanshan Xiang, Hao Xie, Yinyu Mao, Zhenxing Hou, Jian Liu, Xiaotian Huo, Wenqian Yang, Boyi Dong, Guanghui Wang, Chongjian Chen, Gongbo Guo, Yuming Innovation (Camb) Report BACKGROUND: Depression and anxiety are top contributors to non-fatal health loss globally. Several studies have indicated the association between residential greenness and mental health. METHOD: The participants (n = 27,366) were recruited from four counties in Henan Province, China during 2015–2017. Symptoms of depression and anxiety were evaluated using the Patient Health Questionnaire-2 (PHQ-2) and the Generalized Anxiety Disorder-2 (GAD-2) in the baseline survey. The level of residential greenness during the 3-year period before the baseline survey was assessed using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The mixed-effect linear regression model was applied to examine the associations of residential greenness with depression and anxiety. RESULTS: The results of adjusted models showed that the score of PHQ-2 (Δscore and 95% confidence interval [CI]) decreased by −0.024 (−0.041, −0.006) and −0.022 (−0.038, −0.004) with an interquartile range (IQR) increase in NDVI and EVI within a 1,000-m buffer radius, respectively. The score of GAD-2 (Δscore and 95% CI) decreased by −0.024 (−0.040, −0.006) and −0.028 (−0.044, −0.011), in relation to an IQR increase in NDVI and EVI within a 1,000-m buffer radius, respectively. CONCLUSIONS: A higher level of residential greenness was significantly associated with lower risk of depression and anxiety in rural areas of Henan Province. Improving residential greenness accessibility may help to promote the mental health of rural populations. Elsevier 2020-11-02 /pmc/articles/PMC8454668/ /pubmed/34557719 http://dx.doi.org/10.1016/j.xinn.2020.100054 Text en © 2020 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Report Di, Niu Li, Shanshan Xiang, Hao Xie, Yinyu Mao, Zhenxing Hou, Jian Liu, Xiaotian Huo, Wenqian Yang, Boyi Dong, Guanghui Wang, Chongjian Chen, Gongbo Guo, Yuming Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults |
title | Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults |
title_full | Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults |
title_fullStr | Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults |
title_full_unstemmed | Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults |
title_short | Associations of Residential Greenness with Depression and Anxiety in Rural Chinese Adults |
title_sort | associations of residential greenness with depression and anxiety in rural chinese adults |
topic | Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454668/ https://www.ncbi.nlm.nih.gov/pubmed/34557719 http://dx.doi.org/10.1016/j.xinn.2020.100054 |
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