Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data
Meal assistance service is vital for promoting community-based services for the elderly, ensuring the health and well-being of older adults. Taking Beijing, China, as a study area, this paper applied geospatial and statistical methods to examine the spatial pattern and influencing factors for three...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-07-01
|
| Series: | Journal of Asian Architecture and Building Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/13467581.2025.2536778 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849337007715647488 |
|---|---|
| author | Tuke Zheng Xidong Ma Xiaoqing Cheng |
| author_facet | Tuke Zheng Xidong Ma Xiaoqing Cheng |
| author_sort | Tuke Zheng |
| collection | DOAJ |
| description | Meal assistance service is vital for promoting community-based services for the elderly, ensuring the health and well-being of older adults. Taking Beijing, China, as a study area, this paper applied geospatial and statistical methods to examine the spatial pattern and influencing factors for three types of meal assistance facility (MAF) (Type A: MAF of elderly care facilities; Type B: MAF of community dining tables; Type C: MAF of corporate contracting) based on multi-source data. The results showed that: 1) 47.91% of MAFs were located in six central urban districts, with Type A dominating (73.41%), while suburban distribution remained sparse and uneven; 2) MAF development surged after 2015, with 84.63% established thereafter, showing an outward expansion from city center; 3) Subway station accessibility was a positive factor across all types (mean β = 0.124), with additional factors for each type: Type A was further influenced by elderly population density (β = 0.464), neighborhood (β = 0.233), and healthcare (β = 0.094); Type B by elderly population density (β = 0.181) and office space (β = 0.076); Type C by neighborhood (β = 0.259) and GDP (β = 0.127) (all p < 0.01). These insights can offer guidance for future MAF planning. |
| format | Article |
| id | doaj-art-63e9bdfc25aa4c299744893b9f09f610 |
| institution | Kabale University |
| issn | 1347-2852 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Asian Architecture and Building Engineering |
| spelling | doaj-art-63e9bdfc25aa4c299744893b9f09f6102025-08-20T03:44:50ZengTaylor & Francis GroupJournal of Asian Architecture and Building Engineering1347-28522025-07-010011810.1080/13467581.2025.25367782536778Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source dataTuke Zheng0Xidong Ma1Xiaoqing Cheng2Tsinghua UniversityTsinghua UniversityTsinghua UniversityMeal assistance service is vital for promoting community-based services for the elderly, ensuring the health and well-being of older adults. Taking Beijing, China, as a study area, this paper applied geospatial and statistical methods to examine the spatial pattern and influencing factors for three types of meal assistance facility (MAF) (Type A: MAF of elderly care facilities; Type B: MAF of community dining tables; Type C: MAF of corporate contracting) based on multi-source data. The results showed that: 1) 47.91% of MAFs were located in six central urban districts, with Type A dominating (73.41%), while suburban distribution remained sparse and uneven; 2) MAF development surged after 2015, with 84.63% established thereafter, showing an outward expansion from city center; 3) Subway station accessibility was a positive factor across all types (mean β = 0.124), with additional factors for each type: Type A was further influenced by elderly population density (β = 0.464), neighborhood (β = 0.233), and healthcare (β = 0.094); Type B by elderly population density (β = 0.181) and office space (β = 0.076); Type C by neighborhood (β = 0.259) and GDP (β = 0.127) (all p < 0.01). These insights can offer guidance for future MAF planning.http://dx.doi.org/10.1080/13467581.2025.2536778meal assistance facilityspatial patternsinfluencing factorsmulti-source databeijing city |
| spellingShingle | Tuke Zheng Xidong Ma Xiaoqing Cheng Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data Journal of Asian Architecture and Building Engineering meal assistance facility spatial patterns influencing factors multi-source data beijing city |
| title | Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data |
| title_full | Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data |
| title_fullStr | Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data |
| title_full_unstemmed | Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data |
| title_short | Spatial pattern and influencing factors of urban elderly meal assistance facilities: a case study from Beijing, China, based on multi-source data |
| title_sort | spatial pattern and influencing factors of urban elderly meal assistance facilities a case study from beijing china based on multi source data |
| topic | meal assistance facility spatial patterns influencing factors multi-source data beijing city |
| url | http://dx.doi.org/10.1080/13467581.2025.2536778 |
| work_keys_str_mv | AT tukezheng spatialpatternandinfluencingfactorsofurbanelderlymealassistancefacilitiesacasestudyfrombeijingchinabasedonmultisourcedata AT xidongma spatialpatternandinfluencingfactorsofurbanelderlymealassistancefacilitiesacasestudyfrombeijingchinabasedonmultisourcedata AT xiaoqingcheng spatialpatternandinfluencingfactorsofurbanelderlymealassistancefacilitiesacasestudyfrombeijingchinabasedonmultisourcedata |