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- Publisher Website: 10.1080/13607863.2015.1018867
- Scopus: eid_2-s2.0-84959486832
- PMID: 25775108
- WOS: WOS:000370983600010
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Article: Neighborhood support network, perceived proximity to community facilities and depressive symptoms among low socioeconomic status Chinese elders
Title | Neighborhood support network, perceived proximity to community facilities and depressive symptoms among low socioeconomic status Chinese elders |
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Authors | |
Keywords | Neighborhood Perceived walkability Support networks Depressive symptoms Low-SES elders |
Issue Date | 2016 |
Citation | Aging and Mental Health, 2016, v. 20, n. 4, p. 423-431 How to Cite? |
Abstract | Objectives: Depressive symptoms are common in older people; most previous research on elderly depression focused on individual-level characteristics or neighborhood socioeconomic status. Modifiable neighborhood characteristics of older people dwelling in low-income communities are under-studied. This study aims to identify potentially modifiable social and physical neighborhood characteristics that influence depressive symptoms independent of individual-level characteristics among older Chinese.Method: Data came from a cross-sectional survey conducted in four low-income public rental housing estates in Hong Kong in 2012. We interviewed a total of 400 elderly residents. The structured questionnaire covered demographics, activities of daily living, recent fall history, neighborhood support networks, and perceived proximity by walk to community facilities. Multiple regression was used to test whether inclusion of neighborhood factors in addition to individual characteristics increases model fit in explaining depressive symptoms in elders with low socioeconomic status.Results: At individual level, activities of daily living and income significantly predicted depressive symptoms. Receiving support from friends or neighbors is associated with fewer depressive symptoms. However, participants who received organizational support had a 1.17 points of increase on the 15-item Geriatric Depression Scale (GDS-15). At-ease walkable proximity to medical facilities was positively associated with a better GDS score.Conclusion: Neighborhood support networks and perceived proximity by walk to community facilities contribute significantly to depressive symptoms among low-income elders. Programs and policies that facilitate neighborhood support and commuting or promote facility accessibility may help ameliorate depressive symptoms common among low-income elders. |
Persistent Identifier | http://hdl.handle.net/10722/218900 |
ISSN | 2023 Impact Factor: 2.8 2023 SCImago Journal Rankings: 1.403 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, YY | - |
dc.contributor.author | Wong, GHY | - |
dc.contributor.author | Lum, TYS | - |
dc.contributor.author | Lou, VW | - |
dc.contributor.author | Ho, AH | - |
dc.contributor.author | Luo, H | - |
dc.contributor.author | Tong, TL | - |
dc.date.accessioned | 2015-09-18T07:00:03Z | - |
dc.date.available | 2015-09-18T07:00:03Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Aging and Mental Health, 2016, v. 20, n. 4, p. 423-431 | - |
dc.identifier.issn | 1360-7863 | - |
dc.identifier.uri | http://hdl.handle.net/10722/218900 | - |
dc.description.abstract | Objectives: Depressive symptoms are common in older people; most previous research on elderly depression focused on individual-level characteristics or neighborhood socioeconomic status. Modifiable neighborhood characteristics of older people dwelling in low-income communities are under-studied. This study aims to identify potentially modifiable social and physical neighborhood characteristics that influence depressive symptoms independent of individual-level characteristics among older Chinese.Method: Data came from a cross-sectional survey conducted in four low-income public rental housing estates in Hong Kong in 2012. We interviewed a total of 400 elderly residents. The structured questionnaire covered demographics, activities of daily living, recent fall history, neighborhood support networks, and perceived proximity by walk to community facilities. Multiple regression was used to test whether inclusion of neighborhood factors in addition to individual characteristics increases model fit in explaining depressive symptoms in elders with low socioeconomic status.Results: At individual level, activities of daily living and income significantly predicted depressive symptoms. Receiving support from friends or neighbors is associated with fewer depressive symptoms. However, participants who received organizational support had a 1.17 points of increase on the 15-item Geriatric Depression Scale (GDS-15). At-ease walkable proximity to medical facilities was positively associated with a better GDS score.Conclusion: Neighborhood support networks and perceived proximity by walk to community facilities contribute significantly to depressive symptoms among low-income elders. Programs and policies that facilitate neighborhood support and commuting or promote facility accessibility may help ameliorate depressive symptoms common among low-income elders. | - |
dc.language | eng | - |
dc.relation.ispartof | Aging & Mental Health | - |
dc.subject | Neighborhood | - |
dc.subject | Perceived walkability | - |
dc.subject | Support networks | - |
dc.subject | Depressive symptoms | - |
dc.subject | Low-SES elders | - |
dc.title | Neighborhood support network, perceived proximity to community facilities and depressive symptoms among low socioeconomic status Chinese elders | - |
dc.type | Article | - |
dc.identifier.email | Wong, GHY: ghywong@hku.hk | - |
dc.identifier.email | Lum, TYS: tlum@hku.hk | - |
dc.identifier.email | Lou, VW: wlou@hku.hk | - |
dc.identifier.authority | Wong, GHY=rp01850 | - |
dc.identifier.authority | Lum, TYS=rp01513 | - |
dc.identifier.authority | Lou, VW=rp00607 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/13607863.2015.1018867 | - |
dc.identifier.pmid | 25775108 | - |
dc.identifier.scopus | eid_2-s2.0-84959486832 | - |
dc.identifier.hkuros | 253719 | - |
dc.identifier.hkuros | 252102 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 9 | - |
dc.identifier.isi | WOS:000370983600010 | - |
dc.identifier.issnl | 1360-7863 | - |