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Association of residential greenness with geriatric depression among the elderly covered by long-term care insurance in Shanghai

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Abstract

Residential greenness exposure has been linked to a number of physical and mental disorders. Nevertheless, evidence on the association between greenness and geriatric depression was limited and focused on developed countries. This study was aimed to investigate whether the relationship between residential greenness exposure and geriatric depression exists among the elderly with long-term care insurance (LTCI) in Shanghai, China. In 2018, a total of 1066 LTCI elderly from a cross-sectional survey completed a questionnaire in Shanghai. Residential greenness indicators, including normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI), were calculated from the Landsat 8 imagery data in different buffers (100-m, 300-m, and 500-m). Mediation analysis by perceived social support was conducted to explore potential mechanisms underlying the associations. In the fully adjusted model, one IQR increase of NDVI and SAVI in the 300-m buffer size was associated with an 11.9% (PR: 0.881, 95% CI: 0.795, 0.977) and 14.7% (PR: 0.853, 95% CI: 0.766, 0.949) lower prevalence of geriatric depression, respectively. Stronger association was observed in the elderly with lower education level, living in non-central area, and lower family monthly income. Perceived social support significantly mediated 40.4% of the total effect for NDVI 300-m buffer and 40.3% for SAVI 300-m buffer to the greenness-depression association, respectively. Our results indicate the importance of residential greenness exposure to geriatric depression, especially for the elderly with lower education level, living in non-central area, and lower family monthly income. Perceived social support might mediate the association. Well-designed longitudinal studies are warranted to confirm our findings and investigate the underlying mechanisms.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We sincerely express our gratitude to all participants.

Funding

This work was supported by the Supervision and Inspection Institute of Shanghai Municipal Medical Security Bureau, China and the National Natural Science Foundation of China (71974034) (http://www.nsfc.gov.cn).

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Author notes

  1. Wenjia Peng and Hengyuan Shi contributed equally to this work.

Authors and Affiliations

  1. School of Public Health, Fudan University, Shanghai, People’s Republic of China

    Wenjia Peng, Mengying Li, Xinghui Li & Ying Wang

  2. Epidemiology and Health Statistics, School of Public Health, Bengbu Medical College, Bengbu, Anhui, People’s Republic of China

    Hengyuan Shi & Ting Liu

  3. School of Public Health/Key Lab of Health Technology Assessment, National Health and Family Planning Commission of the People’s Republic of China, Fudan University, Shanghai, 200433, People’s Republic of China

    Ying Wang

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  1. Wenjia Peng
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Contributions

Conceptualization, W.Y., L.-M.Y, and L.-X.H.; data management, L.-M.Y. and L.-X.H.; methodology, P.-W.J. and S.-H.Y.; software, P.-W.J. and L.T.; formal analysis, P.-W.J. and S.-H.Y.; writing original draft, P.-W.J. and S.-H.Y.; review and editing, W.Y.; supervision, W.Y.; project administration, W.Y.; funding acquisition: W.Y.

Corresponding author

Correspondence to Ying Wang.

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The study protocol was reviewed and approved by Fudan University Research Ethics Committee.

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A written informed consent with a signature was obtained from all participants in our study. For those who could not write, a fingerprint was replaced instead after the participants have fully understood the information mentioned in the informed consent and agreed to take part in this study as a study subject.

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The authors declare no competing interests.

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Peng, ., Shi, H., Li, M. et al. Association of residential greenness with geriatric depression among the elderly covered by long-term care insurance in Shanghai . Environ Sci Pollut Res 29, 12054–12064 (2022). https://doi.org/10.1007/s11356-021-16585-5

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