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Article(id=1324044560808157789, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202512346, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1766246400000, receivedDateStr=2025-12-21, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793606422855, onlineDateStr=2026-11-02, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793606422855, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793606422855, creator=13701087609, updateTime=1793606422855, updator=13701087609, issue=Issue{id=1324044540067328424, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='8', pageStart='1345', pageEnd='1536', issueExtLink='null', onlineDate='null', pubDate='1777046400000', pubDateStr='2026-04-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793606417910, creator='13701087609', updateTime=1793670137580, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324311799788602160, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324311799788602161, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324044540067328424, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1398, endPage=1403, ext={EN=ArticleExt(id=1324044562741731934, articleId=1324044560808157789, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Associations between built environment and quality of life: Evidence from a Chengdu district, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the impact of urban community built environments on residents' quality of life, and offer empirical support for health-oriented urban planning.

Methods

This study employed a multi-stage random cluster sampling method to survey the permanent residents in 1 401 households across 26 communities and 49 residential areas. Based on the research objectives, 2 086 adult participants were included for analysis. The study integrated multi-source geospatial data and utilized linear mixed-effects model to investigate the association between the built environment and residents' quality of life.

Results

The mental component summary (MCS) score of residents was 49.16±11.58, and the physical component summary (PCS) score was 49.99±10.12. Linear mixed-effects model results showed that green view index (β=2.428, P<0.05), motor vehicle ratio (β=3.180, P<0.05), public transport stop density (β=2.113, P<0.05), road intersection density (β=2.854, P<0.05) and park green space ratio (β=3.048, P<0.01) were positively correlated with MCS; road network density (β=-2.963, P<0.01) and floor area ratio (β=-3.075, P<0.05) were negatively correlated with MCS. For PCS, green view index (β=1.154, P<0.05), motor vehicle ratio (β=2.197, P<0.01) and building density (β=2.018, P<0.05) were positively correlated, while floor area ratio (β=-1.761, P<0.05) was negatively correlated. Additionally, road network density interacted with building density (β=0.979, P<0.05) and green view index (β=-1.112, P<0.05) in affecting PCS.

Conclusion

The built environment of urban communities is closely linked to residents' quality of life. In urban spatial governance, emphasis should be placed on the systematic optimization and synergistic enhancement of various built environment elements to promote community residents' well-being.

, authors=Ke FAN1, Fang LEI2, Yan-qing LI2, Xiao-hui REN1, authorsList=Ke FAN, Fang LEI, Yan-qing LI, Xiao-hui REN, authorCompany=null, correspAuthors=Xiao-hui REN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324044563601564259, articleId=1324044560808157789, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=成都市某区社区建成环境与居民生命质量的相关性研究, columnId=1228016571273113811, journalTitle=现代预防医学, columnName=环境与职业卫生, runingTitle=null, highlight=null, articleAbstract=
目的

探讨城市社区建成环境与居民生命质量的关联，为健康导向的城市规划提供实证依据。

方法

本研究采用多阶段随机整群抽样方法，调查了26个社区、49个小区的1 401户家庭的常住人口。根据研究目的，纳入2 086名18岁及以上调查对象进行分析，整合多源地理空间数据，采用线性混合效应模型探究建成环境与居民生命质量的关联。

结果

居民心理生命质量评分（Mental Component Summary，MCS）为49.16±11.58，躯体生命质量评分（Physical Component Summary，PCS）为49.99±10.12。线性混合效应模型结果显示，草视率（β=2.428，P<0.05）、机动车占比（β=3.180，P<0.05）、公共交通站点密度（β=2.113，P<0.05）、道路交叉口密度（β=2.854，P<0.05）和公园绿地占比（β=3.048，P<0.01）与MCS呈正相关，路网密度（β=-2.963，P<0.01）和容积率（β=-3.075，P<0.05）与MCS呈负相关；草视率（β=1.154，P<0.05）、机动车占比（β=2.197，P<0.01）和建筑密度（β=2.018，P<0.05）与PCS呈正相关，容积率（β=-1.761，P<0.05）与PCS呈负相关；路网密度与建筑密度（β=0.979，P<0.05）、路网密度与草视率（β=-1.112，P<0.05）对PCS具有交互作用。

结论

城市社区建成环境与居民生命质量密切相关。城市社区建设应注重建成环境要素的统筹优化，以促进居民健康。

, authors=范可1, 雷方2, 李彦青2, 任晓晖1, authorsList=范可, 雷方, 李彦青, 任晓晖, authorCompany=null, correspAuthors=任晓晖, authorNote=

范可（2000—），男，硕士在读，研究方向：社会医学

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任晓晖，E-mail：
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(In Chinese), articleTitle=Research on the impact of the built environment in old industrial residential areas on the physical and mental health of residents: evidence from Xiangfang old industrial area in Harbin, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1324044563861611108, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, xref=1., ext=[AuthorCompanyExt(id=1324044563874194021, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, companyId=1324044563861611108, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1324044563886776934, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, companyId=1324044563861611108, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.四川大学华西公共卫生学院/四川大学华西第四医院健康行为与社会医学系，四川　成都　610041)]), AuthorCompany(id=1324044563974857319, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, xref=2., ext=[AuthorCompanyExt(id=1324044563991634536, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, companyId=1324044563974857319, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.成都市金牛区疾病预防控制中心)])], figs=[ArticleFig(id=1324044567401603715, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, language=EN, label=Table 1, caption=

Definitions, measurements and sources of community built environment variables

, figureFileSmall=null, figureFileBig=null, tableContent=
各维度及具体指标定义与度量数据来源
街道形态a
草视率街景图片中植被要素所占的比例（%）百度全景静态图API
机动车占比街景图片中机动化车辆所占的比例（%）
交通道路
公共交通站点密度公交站点和地铁站点的密度（个/km2）
路网密度路网总长度与缓冲区面积的比值（km/km2）高德地图POI、OSM路网数据
道路交叉口密度单位面积的交叉路口数量（个/km2）
土地利用
建筑密度建筑物基底总面积与缓冲区面积的比值（%）天地图平台
容积率建筑物总建筑面积与缓冲区面积的比值
公园绿地
公园绿地占比公园绿地面积所占的比值（%）OSM公园绿地数据
), ArticleFig(id=1324044567489684100, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, language=CN, label=表1, caption=

社区建成环境的变量定义、度量及来源

, figureFileSmall=null, figureFileBig=null, tableContent=
各维度及具体指标定义与度量数据来源
街道形态a
草视率街景图片中植被要素所占的比例（%）百度全景静态图API
机动车占比街景图片中机动化车辆所占的比例（%）
交通道路
公共交通站点密度公交站点和地铁站点的密度（个/km2）
路网密度路网总长度与缓冲区面积的比值（km/km2）高德地图POI、OSM路网数据
道路交叉口密度单位面积的交叉路口数量（个/km2）
土地利用
建筑密度建筑物基底总面积与缓冲区面积的比值（%）天地图平台
容积率建筑物总建筑面积与缓冲区面积的比值
公园绿地
公园绿地占比公园绿地面积所占的比值（%）OSM公园绿地数据
), ArticleFig(id=1324044567565181573, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, language=EN, label=Table 2, caption=

Basic characteristics of the study population and univariate analysis of quality of life scores based on characteristics

, figureFileSmall=null, figureFileBig=null, tableContent=
特征频率（百分比）MCS（均值±标准差）t/FPPCS（均值±标准差）t/FP
性别0.8040.4222.8410.005
男性904（43.3）49.39（11.88）50.71（10.11）
女性1 182（56.7）48.98（11.34）49.44（10.09）
年龄（岁）2.9870.051152.538<0.001
18~44686（32.9）48.44（11.50）53.80（7.36）
45~59587（28.1）49.01（11.50）51.63（8.15）
≥60813（39.0）49.88（11.67）45.59（11.65）
文化程度0.2500.77961.158<0.001
小学及以下420（20.1）48.88（12.01）45.79（12.07）
中学和中专965（46.3）49.34（11.75）49.99（9.76）
大专、本科及以上701（33.6）49.09（11.07）52.51（8.34）
婚姻状况2.1720.08938.110<0.001
未婚239（11.5）47.5753.98（6.94）
已婚1 629（78.1）49.4850.06（10.03）
离异66（3.2）48.1149.81（7.59）
丧偶152（7.3）48.7243.06（12.40）
吸烟情况-2.8110.005-2.4800.013
已戒烟、不吸烟1 768（84.8）48.86（11.61）51.29（9.51）
吸烟318（15.2）50.84（11.22）49.76（10.21）
饮酒情况-4.550<0.001-4.159<0.001
不饮酒1 689（81.0）48.61（11.69）51.88（8.46）
饮酒397（19.0）51.53（10.76）49.55（10.42）
慢性病患病情况-2.1310.03312.702<0.001
无1 116（53.5）48.66（11.55）47.08（11.34）
有970（46.5）49.74（11.58）52.52（8.12）
家庭年收入（万元）5.7300.00112.920<0.001
≤5405（19.4）49.13（12.27）47.85（11.16）
>5~10795（38.1）50.39（11.31）49.65（9.71）
>10~20600（28.8）48.23（11.37）50.78（10.19）
>20286（13.7）47.74（11.44）52.33（8.81）
户籍所在地-1.2540.210-6.534<0.001
成都本地1 612（77.3）48.99（11.49）49.21（10.57）
非成都本地474（22.7）49.75（11.85）52.64（7.87）
), ArticleFig(id=1324044567670039174, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, language=CN, label=表2, caption=

研究人群基本特征及不同特征下生命质量得分的单因素分析

, figureFileSmall=null, figureFileBig=null, tableContent=
特征频率（百分比）MCS（均值±标准差）t/FPPCS（均值±标准差）t/FP
性别0.8040.4222.8410.005
男性904（43.3）49.39（11.88）50.71（10.11）
女性1 182（56.7）48.98（11.34）49.44（10.09）
年龄（岁）2.9870.051152.538<0.001
18~44686（32.9）48.44（11.50）53.80（7.36）
45~59587（28.1）49.01（11.50）51.63（8.15）
≥60813（39.0）49.88（11.67）45.59（11.65）
文化程度0.2500.77961.158<0.001
小学及以下420（20.1）48.88（12.01）45.79（12.07）
中学和中专965（46.3）49.34（11.75）49.99（9.76）
大专、本科及以上701（33.6）49.09（11.07）52.51（8.34）
婚姻状况2.1720.08938.110<0.001
未婚239（11.5）47.5753.98（6.94）
已婚1 629（78.1）49.4850.06（10.03）
离异66（3.2）48.1149.81（7.59）
丧偶152（7.3）48.7243.06（12.40）
吸烟情况-2.8110.005-2.4800.013
已戒烟、不吸烟1 768（84.8）48.86（11.61）51.29（9.51）
吸烟318（15.2）50.84（11.22）49.76（10.21）
饮酒情况-4.550<0.001-4.159<0.001
不饮酒1 689（81.0）48.61（11.69）51.88（8.46）
饮酒397（19.0）51.53（10.76）49.55（10.42）
慢性病患病情况-2.1310.03312.702<0.001
无1 116（53.5）48.66（11.55）47.08（11.34）
有970（46.5）49.74（11.58）52.52（8.12）
家庭年收入（万元）5.7300.00112.920<0.001
≤5405（19.4）49.13（12.27）47.85（11.16）
>5~10795（38.1）50.39（11.31）49.65（9.71）
>10~20600（28.8）48.23（11.37）50.78（10.19）
>20286（13.7）47.74（11.44）52.33（8.81）
户籍所在地-1.2540.210-6.534<0.001
成都本地1 612（77.3）48.99（11.49）49.21（10.57）
非成都本地474（22.7）49.75（11.85）52.64（7.87）
), ArticleFig(id=1324044567787479687, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, language=EN, label=Table 3, caption=

Linear mixed-effects model results of community built environment and residents' quality of life

, figureFileSmall=null, figureFileBig=null, tableContent=
建成环境变量MCS模型PCS模型
模型1未调整β（95%CI）模型2调整β（95%CI）模型3未调整β（95%CI）模型4调整β（95%CI）
草视率2.497a（0.505~4.489）2.428a（0.443~4.413）0.826（-0.248~1.900）1.154a（0.247~2.060）
机动车占比3.264a（0.596~5.932）3.180a（0.522~5.838）1.831a（0.395~3.267）2.197b（0.990~3.404）
公共交通站点密度2.105a（0.270~3.940）2.113a（0.284~3.942）0.586（-0.425~1.597）0.461（-0.389~1.312）
路网密度-2.914a（-5.052~-0.776）-2.963b（-5.094~-0.832）-1.212a（-2.370~-0.054）-0.247（-1.224~0.729）
道路交叉口密度2.959a（0.767~5.151）2.854a（0.671~5.037）1.104（-0.088~2.296）0.398（-0.607~1.403）
建筑密度3.769（0.000~7.538）3.589（-0.159~7.337）1.456（-0.576~3.488）2.018a（0.310~3.726）
容积率-3.240a（-6.214~-0.266）-3.075a（-6.021~-0.129）-1.313（-2.924~0.298）-1.761a（-3.120~-0.402）
公园绿地占比3.079b（1.071~5.087）3.048b（1.047~5.049）0.262（-0.816~1.340）0.642（-0.265~1.549）
边际R20.0890.0970.0240.190
条件R20.2640.2710.0780.222
AIC15 67315 66315 49115 148
), ArticleFig(id=1324044567867171464, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324044560808157789, language=CN, label=表3, caption=

社区建成环境与居民生命质量的线性混合效应模型结果

, figureFileSmall=null, figureFileBig=null, tableContent=
建成环境变量MCS模型PCS模型
模型1未调整β（95%CI）模型2调整β（95%CI）模型3未调整β（95%CI）模型4调整β（95%CI）
草视率2.497a（0.505~4.489）2.428a（0.443~4.413）0.826（-0.248~1.900）1.154a（0.247~2.060）
机动车占比3.264a（0.596~5.932）3.180a（0.522~5.838）1.831a（0.395~3.267）2.197b（0.990~3.404）
公共交通站点密度2.105a（0.270~3.940）2.113a（0.284~3.942）0.586（-0.425~1.597）0.461（-0.389~1.312）
路网密度-2.914a（-5.052~-0.776）-2.963b（-5.094~-0.832）-1.212a（-2.370~-0.054）-0.247（-1.224~0.729）
道路交叉口密度2.959a（0.767~5.151）2.854a（0.671~5.037）1.104（-0.088~2.296）0.398（-0.607~1.403）
建筑密度3.769（0.000~7.538）3.589（-0.159~7.337）1.456（-0.576~3.488）2.018a（0.310~3.726）
容积率-3.240a（-6.214~-0.266）-3.075a（-6.021~-0.129）-1.313（-2.924~0.298）-1.761a（-3.120~-0.402）
公园绿地占比3.079b（1.071~5.087）3.048b（1.047~5.049）0.262（-0.816~1.340）0.642（-0.265~1.549）
边际R20.0890.0970.0240.190
条件R20.2640.2710.0780.222
AIC15 67315 66315 49115 148
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成都市某区社区建成环境与居民生命质量的相关性研究
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范可 1 , 雷方 2 , 李彦青 2 , 任晓晖 1
现代预防医学 | 环境与职业卫生 2026,53(8): 1398-1403
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现代预防医学 |环境与职业卫生 2026 , 53 (8) : 1398 -1403
成都市某区社区建成环境与居民生命质量的相关性研究
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范可（2000—），男，硕士在读，研究方向：社会医学

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范可1, 雷方2, 李彦青2, 任晓晖1
作者信息
  • 1.四川大学华西公共卫生学院/四川大学华西第四医院健康行为与社会医学系，四川　成都　610041
  • 2.成都市金牛区疾病预防控制中心
通讯作者:
任晓晖，E-mail：
作者简介:

范可（2000—），男，硕士在读，研究方向：社会医学

Associations between built environment and quality of life: Evidence from a Chengdu district
Ke FAN1, Fang LEI2, Yan-qing LI2, Xiao-hui REN1
Affiliations
  • Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2026-04-25 doi: 10.20043/j.cnki.MPM.202512346
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摘要
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目的

探讨城市社区建成环境与居民生命质量的关联，为健康导向的城市规划提供实证依据。

方法

本研究采用多阶段随机整群抽样方法，调查了26个社区、49个小区的1 401户家庭的常住人口。根据研究目的，纳入2 086名18岁及以上调查对象进行分析，整合多源地理空间数据，采用线性混合效应模型探究建成环境与居民生命质量的关联。

结果

居民心理生命质量评分（Mental Component Summary，MCS）为49.16±11.58，躯体生命质量评分（Physical Component Summary，PCS）为49.99±10.12。线性混合效应模型结果显示，草视率（β=2.428，P<0.05）、机动车占比（β=3.180，P<0.05）、公共交通站点密度（β=2.113，P<0.05）、道路交叉口密度（β=2.854，P<0.05）和公园绿地占比（β=3.048，P<0.01）与MCS呈正相关，路网密度（β=-2.963，P<0.01）和容积率（β=-3.075，P<0.05）与MCS呈负相关；草视率（β=1.154，P<0.05）、机动车占比（β=2.197，P<0.01）和建筑密度（β=2.018，P<0.05）与PCS呈正相关，容积率（β=-1.761，P<0.05）与PCS呈负相关；路网密度与建筑密度（β=0.979，P<0.05）、路网密度与草视率（β=-1.112，P<0.05）对PCS具有交互作用。

结论

城市社区建成环境与居民生命质量密切相关。城市社区建设应注重建成环境要素的统筹优化，以促进居民健康。

建成环境  /  社区居民  /  生命质量
Objective

To investigate the impact of urban community built environments on residents' quality of life, and offer empirical support for health-oriented urban planning.

Methods

This study employed a multi-stage random cluster sampling method to survey the permanent residents in 1 401 households across 26 communities and 49 residential areas. Based on the research objectives, 2 086 adult participants were included for analysis. The study integrated multi-source geospatial data and utilized linear mixed-effects model to investigate the association between the built environment and residents' quality of life.

Results

The mental component summary (MCS) score of residents was 49.16±11.58, and the physical component summary (PCS) score was 49.99±10.12. Linear mixed-effects model results showed that green view index (β=2.428, P<0.05), motor vehicle ratio (β=3.180, P<0.05), public transport stop density (β=2.113, P<0.05), road intersection density (β=2.854, P<0.05) and park green space ratio (β=3.048, P<0.01) were positively correlated with MCS; road network density (β=-2.963, P<0.01) and floor area ratio (β=-3.075, P<0.05) were negatively correlated with MCS. For PCS, green view index (β=1.154, P<0.05), motor vehicle ratio (β=2.197, P<0.01) and building density (β=2.018, P<0.05) were positively correlated, while floor area ratio (β=-1.761, P<0.05) was negatively correlated. Additionally, road network density interacted with building density (β=0.979, P<0.05) and green view index (β=-1.112, P<0.05) in affecting PCS.

Conclusion

The built environment of urban communities is closely linked to residents' quality of life. In urban spatial governance, emphasis should be placed on the systematic optimization and synergistic enhancement of various built environment elements to promote community residents' well-being.

Built environment  /  Community residents  /  Quality of life
范可, 雷方, 李彦青, 任晓晖. 成都市某区社区建成环境与居民生命质量的相关性研究. 现代预防医学, 2026 , 53 (8) : 1398 -1403 . DOI: 10.20043/j.cnki.MPM.202512346
Ke FAN, Fang LEI, Yan-qing LI, Xiao-hui REN. Associations between built environment and quality of life: Evidence from a Chengdu district[J]. Modern Preventive Medicine, 2026 , 53 (8) : 1398 -1403 . DOI: 10.20043/j.cnki.MPM.202512346
正文
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随着疾病谱改变、人口老龄化程度加剧及积极健康观的普及，生命质量作为综合评价个体和群体主观健康状况的重要概念和指标，在医学研究和实践中得到广泛应用[1]。生命质量不仅受年龄、疾病、医疗干预、个体社会特征等因素影响[2]，也与个体日常所在的社区环境密切相关[3]。其中，社区建成环境是社区环境的重要组成部分。社区建成环境是由土地利用、交通系统、建筑形态以及公共服务设施等维度共同构成的物质空间系统[4]。现有研究表明，社区建成环境与居民的健康相关行为（如社会交往、出行方式、体力活动水平）[5-8]及健康结局（如身体质量指数、心血管疾病风险、心理健康状况）[9-11]具有相关性。但现有研究多聚焦于单一行为或特定疾病维度，关于社区建成环境与生命质量的研究相对不足。同时，在研究方法上多采用单一层次方法，忽略了个体嵌套于社区的分层数据结构特征，也未充分考虑建成环境各要素之间的协同效应。本研究以成都市某区为例，整合居民健康调查数据与城市社区地理空间数据，运用线性混合效应模型，探究城市社区建成环境与居民生命质量的关联，为构建健康导向的社区环境建设提供理论依据。
1　资料与方法
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1.1　数据来源
1.1.1　个体层面居民基本信息相关数据来源
本研究居民社会人口学特征和生命质量等数据来源于“成都市某区慢性病综合防控社会因素调查项目”。该项目于2023年12月至2024年2月进行调查，该区13个街道均纳入调查，采用多阶段随机整群抽样方法，按照各街道人口规模比例，每个街道随机抽取1-3个社区，每个社区随机抽取1-2个小区，每个小区随机抽取单数楼栋，该楼栋所有家户纳入调查。由统一培训的调查员利用结构式电子问卷入户进行面对面访谈，收集全部常住家庭成员信息。电子问卷为自行设计的《成都市某区慢性病综合防控社会因素调查表》，调查内容涵盖性别、年龄、文化程度、婚姻状况、户籍地、慢性病患病情况、吸烟饮酒史、家庭年收入、职业和生命质量等，所有受访者均已签署知情同意书。最终调查了26个社区、49个小区的1 401户家庭，共2 800人。基于本研究目的，纳入标准为：（1）在调查地居住半年及以上居民；（2）年龄≥18岁；排除标准为：（1）生命质量数据不完整的参与者；（2）调查人数低于10人的小区。最终纳入47个小区中18岁及以上的居民共计2 086人进行分析。
样本量的估算依据计量资料横断面调查的通用公式，参数设定如下：显著性水平α为0.05（双侧检验），对应的zα/2=1.96，最大允许误差ε设定为0.02，结局指标生命质量的期望均值μ参考量表常模设定为50，标准差σ为10，据此计算变异系数CV=0.2。将上述参数代入公式计算为384人，本研究样本量充足。
1.1.2　社区层面客观建成环境数据来源
本研究系统收集调查社区的建成环境数据，数据时间与居民健康调查数据保持一致。数据来源包括百度全景静态图API、OpenStreetMap平台（OSM）、国家地理信息公共服务天地图平台及高德地图POI兴趣点数据。本研究经过四川大学华西公共卫生学院伦理审查委员会批准（Gwll2025059）。
1.2　研究变量及定义
1.2.1　生命质量
生命质量的测定采用《成都市某区慢性病综合防控社会因素调查表》中的中文版SF-12量表（第二版）。该量表共包含12个条目，涵盖八个维度，各条目参照公式转换为标准化得分[12]，归纳为躯体生命质量PCS评分与心理生命质量MCS评分两个方面，分值范围均为0~100分，得分越高代表其对应的生命质量越好。该量表在中国人群研究中具有良好的信效度[13]。本研究中，MCS与PCS的克朗巴赫α系数分别为0.717和0.818，内部一致性较好。
1.2.2　社区建成环境
基于既往研究和本研究研究目的[3,14]，本研究从街道形态、交通道路、土地利用、绿色空间四个维度刻画社区建成环境特征，各维度具体指标及其定义、度量和来源见表1。
同时，本研究基于15分钟生活圈理念[15]，依托OSM路网数据和ArcGIS软件的网络分析功能生成社区800米网络缓冲区，作为基本地理分析单元。该方法较传统欧氏距离半径缓冲区能更准确地代表居民日常活动主要范围。所有建成环境指标均在缓冲区范围内进行空间计算，同一社区内的居民所对应的建成环境变量取值相同。
1.2.3　控制变量
本研究控制了一系列个体层面的人口学与社会经济变量，包括性别、年龄分组、文化程度（小学及以下：含文盲与小学；中学/中专：包括中学、中专与技校；大专/本科及以上）、婚姻状况、家庭年收入等级、以及慢性病患病情况、吸烟情况、饮酒情况以及是否成都本地户籍。
1.3　统计分析
本研究采用R 4.3.1软件进行统计分析，分类变量采用频数（百分比）表示，连续变量以表示，组间比较采用两样本t检验或方差分析。
针对数据“个体-社区”两水平嵌套的层级结构，本研究运用R 4.3.1的lme4软件包，基于限制性最大似然估计拟合线性混合效应模型：首先，构建零模型，计算组内相关系数，评估社区层级的方差贡献；其次，建立随机截距模型，依次纳入建成环境变量和显著的个体基本特征，分析建成环境对健康结局的主效应；同时汇报决定系数（边际R2与条件R2）和赤池信息准则（Akaike information criterion，AIC）以判断模型解释力和拟合效果。第三，进一步纳入了建成环境变量之间的交互项，探究不同建成环境要素之间可能存在的交互作用。
为消除各建成环境指标间的量纲差异，使其回归系数具备可比性，所有建成环境变量均进行Z-score标准化处理，转化为均值为0、标准差为1的标准化变量。检验水准α=0.05。
2　结果
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2.1　研究对象基本特征与生命质量得分
本研究共纳入2 086名研究对象，其中女性占56.7%，60岁及以上人群占比最高（39.0%），文化程度以中学/中专者居多（46.3%），已婚者占78.1%，吸烟者占15.2%，饮酒者占19.0%，慢性病患病率为46.5%。家庭年收入以中低收入组为主（38.1%），本地居民占77.3%（表2）。
调查对象PCS得分为49.99±10.12，MCS得分为49.16±11.58。不同性别、年龄、文化程度、婚姻状况、吸烟状况、饮酒状况、慢性病患病情况、家庭年收入、户籍地的调查对象PCS得分有差异（P<0.05）；而MCS得分的组间差异则体现在吸烟状况、饮酒状况、慢性病患病情况及家庭年收入四个维度（P<0.05）（表2）。
2.2　社区建成环境基本情况
社区建成环境特征测度显示，街道形态方面：草视率为1.3%±0.8%，机动车占比为3.3%±1.2%；交通道路方面：公共交通站点密度为（11.0±5.3）个/km2，路网密度为（26.5±8.3）km/km2，道路交叉口密度为（65.9±52.2）个/km2；土地利用强度方面：建筑密度为24.0%±8.5%，容积率为1.41±0.46；绿色空间方面：公园绿地占比为4.3%±6.0%。为诊断多重共线性，计算了所有建成环境变量的方差膨胀因子，结果显示所有变量VIF值介于1.69~5.53，均小于10，不存在严重多重共线性问题。
2.3　社区建成环境对居民生命质量影响的线性混合效应模型分析
首先，构建零模型，计算组内相关系数，零模型分析结果显示，MCS的组内相关系数（ICC）为0.265（P<0.001），表明26.5%的变异由社区层面因素所解释；PCS的ICC为0.079（P<0.001），其总变异的7.9%来源于社区层面因素。因此，有必要采用线性混合效应模型进行后续分析。
随后建立随机截距模型，仅纳入建成环境变量，构建了未调整模型（针对MCS的模型1与针对PCS的模型3），再在未调整模型基础上分别纳入单因素分析中显著的控制变量，得到完整调整模型（模型2与模型4）。线性混合效应模型结果如表3所示。MCS方面，模型1显示，草视率（β=2.497，P<0.05）、机动车占比（β=3.264，P<0.05）、公共交通站点密度（β=2.105，P<0.05）、道路交叉口密度（β=2.959，P<0.05）和公园绿地占比（β=3.079，P<0.01）均对MCS有显著正向效应，路网密度（β=-2.914，P<0.01）和容积率（β=-3.240，P<0.05）对MCS有显著负向影响。建筑密度（β=3.769，P=0.055）对MCS的影响不显著。模型2显示，草视率（β=2.428，P<0.05）、机动车占比（β=3.180，P<0.05）、公共交通站点密度（β=2.113，P<0.05）、道路交叉口密度（β=2.854，P<0.05）及公园绿地占比（β=3.048，P<0.01）对MCS仍为显著正向效应，路网密度（β=-2.963，P<0.01）和容积率（β=-3.075，P<0.05）仍为显著负向影响。建筑密度（β=3.589，P=0.067）对MCS的影响不显著。纳入控制变量后，建成环境对MCS的影响未发生明显变化。
PCS方面，模型3与模型4结果对比显示：模型3中与PCS无显著关联的草视率、建筑密度和容积率，在模型4中均呈现显著关联，具体表现为草视率（β=1.154，P<0.05）、建筑密度（β=2.018，P<0.05）与PCS呈正相关，容积率（β=-1.761，P<0.05）与PCS为负相关；同时，机动车占比的正向关联进一步增强（模型3：β=1.831，P<0.05，模型4：β=2.197，P<0.01）。这些变化提示控制个体混杂因素后，社区建成环境指标与PCS的真实关联得以凸显。公共交通站点密度、道路交叉口密度及公园绿地占比与PCS的关联始终无统计学意义（P>0.05）。模型比较显示，在纳入控制变量后，模型解释力和拟合效果均改善。
最后，基于模型2和模型4，依次将社区建成环境8个特征变量的所有两交互项独立地纳入模型进行检验。结果提示，在检验的所有交互项中，社区建成环境各变量对于MCS未见显著交互项，而路网密度与建筑密度的交互项对PCS具有正向交互作用（β=0.979，P<0.05），路网密度与草视率的交互项对PCS呈现负向交互作用（β=-1.112，P<0.05）。
3　讨论
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本研究调查显示，成都市某区18岁及以上社区居民的躯体与心理健康得分均接近量表理论中值50分，整体处于中等水平，与既往研究结果相近[16]；城市社区建成环境特征亦与既往研究同类城市社区较为相近[16]，表明本研究在典型城市环境中具有良好的可比性。
本文研究发现，草视率与公园绿地占比与MC呈正相关，草视率与PCS呈正相关，与既往研究结论相似，其关联可能在于绿色空间能促进居民的身体活动和社交活动，舒缓心理压力，有益于身心健康[17]。道路交叉口密度、机动车占比和公共交通站点密度均与MCS呈正相关，机动车占比和建筑密度与PCS同样为正相关，可能是由于建筑密度较高的区域通常对应更完善的公共服务设施配套，良好的交通建设有助于提高医疗、文化和休闲等各类服务设施的可达性，同时促进居民参与休闲性身体活动，对身心健康产生积极影响[18]，然而，这种关联也可能受到未充分控制的混杂因素的影响，仍需进一步控制相关混杂变量加以验证。过高的路网密度可能因交通噪音、污染排放和影响睡眠质量等因素对MCS产生不利影响[19]。过高的容积率则可能因为过度开发导致的拥挤感与公共空间减少，造成体力活动减少、心理压力加剧，进而对身心健康产生负面影响[20]。
同时，本研究发现，PCS与社区建成环境要素间交互作用存在关联。在路网密集的区域，建筑密度与PCS的正向关联更为明显，这可能是通过提升公共服务可达性和促进日常身体活动实现的。另一方面，在路网密集区域，草视率与PCS的正向关联会减弱，可能与密集路网带来的交通污染和噪音干扰削弱了绿地的健康促进作用有关。心理健康方面未见显著交互项，该结果与现有研究揭示的模式相符：建成环境变量间的交互效应在解释身体健康结局时更为显著，而在心理健康方面相对有限，原因可能在于建成环境对于心理健康影响的作用模式有所不同，显著的交互作用更常见于如人口密度、环境安全感知等涉及社会互动与主观体验的环境特征[21]，而非本研究主要关注的、与空间形态相关的建成环境变量之间的交互。
本研究存在一些局限性：首先，样本社区均来自于成都市同一行政区，社区间的建成环境和人群健康状况差异较小，可能弱化了社区建成环境与生命质量的关联强度；其次，研究仅基于单一尺度（800米网络缓冲区）进行分析，未能考察不同空间尺度下建成环境与生命质量关联的差异。此外，本研究为横断面研究设计，无法推断建成环境与居民生命质量之间的因果关系，也未充分控制混杂因素，如社区居住时长、职业等。
综上所述，本研究发现多项社区建成环境要素与居民生命质量相关，且要素间具有一定的交互效应。研究结果提示，在城市社区空间治理中，应综合考虑各类建成环境要素的规划和协调发展，具体包括：构建多层次绿色空间体系，将公园绿地与街道绿化有机结合；优化路网结构与公共交通可达性；合理控制建筑容积率；优化建成环境布局，以提高交通道路和建筑功能区的健康协同作用，规避交通道路对绿地健康效用的削弱，从而促进社区居民健康相关生命质量。

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2026年第53卷第8期
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doi: 10.20043/j.cnki.MPM.202512346
  • 接收时间：2025-12-21
  • 首发时间：2026-11-02
  • 出版时间：2026-04-25
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  • 收稿日期：2025-12-21
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    1.四川大学华西公共卫生学院/四川大学华西第四医院健康行为与社会医学系，四川　成都　610041
    2.成都市金牛区疾病预防控制中心

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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