城市居民日常身体活动时空分异特征及影响因素
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摘要
依托南京主城区居民日常身体活动调查数据,基于身体活动时空维度,挖掘城市居民日常身体活动时空分异特征,并采用混合效应模型探究身体活动分异的影响因素。研究表明:①居民日常身体活动时空异质特征明显。工作日/非工作日不同类型身体活动时间安排及个体间差异均显著;工作性、交通性、家务性身体活动空间制约明显,而休闲性身体活动空间分布更具弹性;与工作日相比,非工作日不同类型身体活动空间范围变化收敛与扩散特征并存。②活动空间范围、个人社会经济属性、自身健康状况对居民日常身体活动分异均具有显著影响。具体而言,居民日常活动空间范围决定身体活动的空间适应与选择;社会分工差异导致不同性别、年龄人群身体活动具有指向性;身体活动时间出现与个人社会经济实力倒置现象;而良好健康状态会激励居民日常身体活动的保持。
Promoting physical activity is a priority of public health strategy for preventing major chronic diseases because of its popularity and known health benefits. Therefore, the related research of physical activity is an important field of study, and it has become a hot theme between multiple disciplines at home and abroad. The point-based locations regularly visited and the time spend in the past week by 1 102 participants were collected in the main urban area of Nanjing, this study analyzes the spatial-temporal characteristics of daily physical activity of urban residents. The mixed effect model was used to furtherly explore associations between the range of physical activity space, social-demographic characteristics, health status and the difference of self-reported physical activity. The results show that: 1) The spatial and temporal heterogeneity of residents' daily physical activity is obvious. There were significant differences in time allocation of different types of physical activity and individuals between weekday and weekend. Work-, traffic-, housework-physical activity space are obviously restricted, while leisure-physical activity space distribution is more flexible. In addition, compared with the weekday, there are convergence and diffusion characteristics in the changes of range of different types physical activity space in weekend. 2) The range of physical activity space, individual social-demographic attributes,and their own health status all have significant effects on the difference of residents' daily physical activity.Specifically,, considering the locations of physical activity visited, this study found that the spatial scope of daily physical activity determine the spatial adaptation and choice of physical activity. Meanwhile, differences in social division of labor lead to physical activity in different sex and age groups. Besides, personal social and economic strength is negatively correlated with physical activity. However, good health may particularly encourages residents to maintain or increase more daily physical activity.
Promoting physical activity is a priority of public health strategy for preventing major chronic diseases because of its popularity and known health benefits. Therefore, the related research of physical activity is an important field of study, and it has become a hot theme between multiple disciplines at home and abroad. The point-based locations regularly visited and the time spend in the past week by 1 102 participants were collected in the main urban area of Nanjing, this study analyzes the spatial-temporal characteristics of daily physical activity of urban residents. The mixed effect model was used to furtherly explore associations between the range of physical activity space, social-demographic characteristics, health status and the difference of self-reported physical activity. The results show that: 1) The spatial and temporal heterogeneity of residents' daily physical activity is obvious. There were significant differences in time allocation of different types of physical activity and individuals between weekday and weekend. Work-, traffic-, housework-physical activity space are obviously restricted, while leisure-physical activity space distribution is more flexible. In addition, compared with the weekday, there are convergence and diffusion characteristics in the changes of range of different types physical activity space in weekend. 2) The range of physical activity space, individual social-demographic attributes,and their own health status all have significant effects on the difference of residents' daily physical activity.Specifically,, considering the locations of physical activity visited, this study found that the spatial scope of daily physical activity determine the spatial adaptation and choice of physical activity. Meanwhile, differences in social division of labor lead to physical activity in different sex and age groups. Besides, personal social and economic strength is negatively correlated with physical activity. However, good health may particularly encourages residents to maintain or increase more daily physical activity.
引文
[1]世界卫生组织.身体活动[EB/OL].http://www.who.int/mediacentre/factsheets/fs385/zh/,2018-06-10.[World Health Organization.Physical activity.http://www.who.int/mediacentre/factsheets/fs385/zh/,2018-06-10.]
[2] Lee I M,Skerrett P J.Physical activity and all-cause mortality:What is the dose-response relation?[J].Medicine and Science in Sports and Exercise, 2001, 33(6 Suppl):S459-S471.
[3] Warburton D E, Nicol C W, Bredin S S. Health benefits of physical activity:The evidence[J]. Cmaj,2006,174(6):801-809.
[4] Kohl H W, Craig C L, Lambert E V et al. The pandemic of physical inactivity:Global action for public health[J].Lancet,2012,380(9838):294-305.
[5] Bauman A, Bull F,Tien C et al.The international prevalence study on physical activity:Results from 20 countries[J].International Journal of Behavioral Nutrition and Physical Activity,2009,6(1):21.
[6] Wolff-Hughes D L,Troiano R P, Boyer W R et al.Use of population-referenced total activity counts percentiles to assess and classify physical activity of population groups[J].Preventive Medicine, 2016, 87:35-40.
[7] Nguyen Q C,Kath S,Meng H W et al.Leveraging geotagged Twitter data to examine neighborhood happiness,diet,and physical activity[J]. Applied Geography,2016,73:77-88.
[8]齐兰兰,周素红.邻里建成环境对居民外出型休闲活动时空差异的影响:以广州市为例[J].地理科学, 2018, 38(1):31-40.[Qi Lanlan, Zhou Suhong. The influence of neighborhood built environments on the spatial-temporal characteristics of residents'daily leisure activities:A case study of Guangzhou. Scientia Geographica Sinica, 2018, 38(1):31-40.]
[9]李米环,李国强,江崇民.2013年南京、上海城区居民体力活动模式及其与超重/肥胖关系[J].卫生研究,2017,46(2):331-336.[Li Mihuan,Li Guoqiang,Jiang Chongmin.Physical activity patterns and their relationship with overweight/obesity in urban residents of Nanjing and Shanghai in 2013.Journal of Hygiene Research,2017,46(2):331-336.]
[10] Schuna J M, Johnson W D, Tudor-Locke C. Adult self-reported and objectively monitored physical activity and sedentary behavior:NHANES 2005-2006[J]. International Journal of Behavioral Nutrition and Physical Activity, 2013, 10(1):126.
[11] Juneau C E,Potvin L.Trends in leisure-,transport-,and work-related physical activity in Canada 1994-2005[J].Preventive Medicine,2010,51(5):384-386.
[12] Silva K S, Garcia L M T, Rabacow F M et al. Physical activity as part of daily living:Moving beyond quantitative recommendations[J]. Preventive Medicine, 2017, 96:160-162.
[13] Althoff T, Sosi?R, Hicks J L et al. Large-scale physical activity data reveal worldwide activity inequality[J]. Nature, 2017, 547(7663):336-339.
[14]张彦峰,江崇民,蔡睿,等.中国国民体力活动水平的区域特征研究[J].体育科学, 2012, 32(9):3-10, 22.[Zhang Yanfeng,Jiang Chongmin, Cai Rui et al. Regional characteristics of the national physical activity level in China. China Sport Science,2012, 32(9):3-10, 22.]
[15] Matisziw T C, Nilon C H, Wilhelm Stanis S A et al. The right space at the right time:The relationship between children's physical activity and land use/land cover[J]. Landscape and Urban Planning, 2016, 151:21-32.
[16] Hillsdon M, Coombes E, Griew P et al. An assessment of the relevance of the home neighbourhood for understanding environmental influences on physical activity:How far from home do people roam?[J]. International Journal of Behavioral Nutrition and Physical Activity, 2015, 12:100.
[17] Stewart T, Duncan S, Schipperijn J. Adolescents who engage in active school transport are also more active in other contexts:A space-time investigation[J]. Health&Place, 2017, 43:25-32.
[18]关美宝,郭文伯,柴彦威.人类移动性与健康研究中的时间问题[J].地理科学进展,2013,32(9):1344-1351.[Guan Meibao,Guo Wenbo,Chai Yanwei.Temporally integrated human mobility and health research.Progress in Geography,2013,32(9):1344-1351.]
[19] Hurvitz P M, Moudon A V, Kang B et al. How far from home?The locations of physical activity in an urban US setting[J]. Preventive Medicine, 2014, 69:181-186.
[20] Feuillet T, Charreire H, Menai M et al. Spatial heterogeneity of the relationships between environmental characteristics and active commuting:Towards a locally varying social ecological model[J]. International Journal of Health Geographics, 2015, 14:12.
[21] Feuillet T, Salze P, Charreire H et al. Built environment in local relation with walking:Why here and not there?[J]. Journal of Transport&Health, 2016, 3(4):500-512.
[22] Perchoux C, Kestens Y, Brondeel R et al. Accounting for the daily locations visited in the study of the built environment correlates of recreational walking(the RECORD Cohort Study)[J].Preventive Medicine, 2015, 81:142-149.
[23] Saarloos D, Kim J E, Timmermans H. The built environment and health:introducing individual space-time behavior[J]. International Journal of Environmental Research and Public Health,2009, 6(6):1724-1743.
[24] Chaix B, Méline J, Duncan S et al. Neighborhood environments, mobility, and health:Towards a new generation of studies in environmental health research[J]. Revue d'épidémiologie Et De SantéPublique, 2013, 61:S139-S145.
[25] MacIntyre S, Ellaway A, Cummins S. Place effects on health:How can we conceptualise, operationalise and measure them?[J]. Social Science&Medicine, 2002, 55(1):125-139.
[26] Perchoux C, Chaix B, Brondeel R et al. Residential buffer, perceived neighborhood, and individual activity space:New refinements in the definition of exposure areas—The RECORD Cohort Study[J]. Health&Place, 2016, 40:116-122.
[27] Trost S G,Owen N,Bauman A E et al.Correlates of adults'participation in physical activity:Review and update[J].Medicine&Science in Sports&Exercise,2002,34(12):1996-2001.
[28] Plotnikoff R C, Mayhew A, Birkett N et al. Age, gender, and urban-rural differences in the correlates of physical activity[J].Preventive Medicine, 2004, 39(6):1115-1125.
[29] Florindo A A, Guimar?es V V, Cesar C L G et al. Epidemiology of leisure, transportation, occupational, and household physical activity:Prevalence and associated factors[J]. Journal of Physical Activity and Health, 2009, 6(5):625-632.
[30] Tigbe W W, Lean M E J, Granat M H. A physically active occupation does not result in compensatory inactivity during out-of-work hours[J]. Preventive Medicine, 2011, 53(1/2):48-52.
[31] Ivory V C, Blakely T, Pearce J et al. Could strength of exposure to the residential neighbourhood modify associations between walkability and physical activity?[J]. Social Science&Medicine, 2015, 147:232-241.
[32] Stahl S T, Albert S M. Gender differences in physical activity patterns among older adults who fall[J]. Preventive Medicine,2015, 71:94-100.
[33] Cerin E, Mitá?J, Cain K L et al. Do associations between objectively-assessed physical activity and neighbourhood environment attributes vary by time of the day and day of the week?IPEN adult study[J]. International Journal of Behavioral Nutrition and Physical Activity, 2017, 14:34.
[34]南京日报.南京市2018年国民经济和社会发展统计公报[EB/OL].http://njrb.njdaily.cn/njrb/html/2019-04/01/content_532184.htm?div=2.2018-06-10.[The Nanjing Daily.Nanjing statistical bulletin on national economic and social development 2018.http://njrb.njdaily.cn/njrb/html/2019-04/01/content_532184.htm?div=2.2018-06-10.]
[35]南京市统计局.南京统计年鉴(2017)[M/OL]. http://221.226.86.104/file/nj2004/2017/index.htm.[Nanjing Statistical Bureau. Statistical yearbook of Nanjing(2017). http://221.226.
[36]南京市人民政府.南京市全民健身实施计划[EB/OL].http://www.nanjing.gov.cn/xxgk/szf/201701/t20170126_435 1268.html.2018-06-10.[The People's Government of Nanjing. Implementation plan of national fitness program in Nanjing. http://www.nj.gov.cn/xxgk/szf/201701/t20170126_4351267.html.2018-06-10.]
[37]南京市卫生和生育计划委员会.2017年南京市户籍居民病、伤死亡原因简析[EB/OL]. http://wjw.nanjing.gov.cn/njswshjhsywyh/201805/t20180504_5387258.html.2018-06-10.[The Municipal Health and Reproductive Planning Committee of Nanjing.Analysis on causes of death and injury of registered residents in Nanjing in 2017. http://wjw.nanjing.gov.cn/njswshjhsywyh/201805/t201-80504_5387258.html.2018-06-10.]
[38] Craig C, Marshall A, SJ?STR?M M et al. International physical activity questionnaire:12-country reliability and validity.Medicine&Science in Sports&Exercise, 2003, 35(8):1381-1395.86.104/file/nj2004/2017/index.htm.]
[39]陈春,塔吉努尔·海力力,陈勇.女性老年人肥胖的建成环境影响因素及规划响应研究[J].人文地理,2018,33(4):76-81.[Chen Chun,Hailili Tajnur, ChenYong. Built environment’s influence on obesity of the older women and its planning responses.Human Geography, 2018,33(4):76-81.]
[40]王晓娟.混合效应模型中的参数估计[D].杭州:浙江大学,2013.[Wang Xiaojuan.Parameter estimation in mixed effect models.Hangzhou:Zhejiang University, 2013.]
[41]郝静,孙成,郭兴宇,等.京津冀内陆平原区PM2.5浓度时空变化定量模拟[J].环境科学,2018,39(4):1455-1465.[Hao Jing,Sun Cheng,Guo Xingyu et al.Simulation of the spatio-temporally resolved PM2.5aerosol mass concentration over the inland plain of the Beijing-Tianjin-Hebei region. Environmental Science,2018,39(4):1455-1465.]
(1)根据南京统计年鉴(2017年)[35],2016年南京市三次产业占比(单位:%)为2.4∶39.2∶58.4,全市城镇非私营单位从业人员中从事服务业人员占比达到55.74%,推断出南京市就业结构以服务型职业为主。
(2)无重大疾病,行动方便且能够独立完成问卷调研的常住居民。
(3)假定每人每天至少有8 h睡眠时间,个体报告的全部身体活动每天累计时间总和则不能超过960 min。
(1)为减少原始数据因数值差异大带来的估计误差,对Y值进行标准化处理,即通过每一变量原值与其平均值之差除以该变量的标准差获取新值。
(2)1 000 m阈值选择主要考虑:一是在居民可接受的15 min步行范围内;二是与居民日常发生联系最多(如买菜、送小孩上下学、散步等)的日常生活空间范围。
(1)为解决解释变量和交互项共线性问题,对交互项变量做去中心化处理。在性别和其它变量交互分析中,以男性作为参照,分别测度女性样本和年龄、空间距离的交互作用。
[2] Lee I M,Skerrett P J.Physical activity and all-cause mortality:What is the dose-response relation?[J].Medicine and Science in Sports and Exercise, 2001, 33(6 Suppl):S459-S471.
[3] Warburton D E, Nicol C W, Bredin S S. Health benefits of physical activity:The evidence[J]. Cmaj,2006,174(6):801-809.
[4] Kohl H W, Craig C L, Lambert E V et al. The pandemic of physical inactivity:Global action for public health[J].Lancet,2012,380(9838):294-305.
[5] Bauman A, Bull F,Tien C et al.The international prevalence study on physical activity:Results from 20 countries[J].International Journal of Behavioral Nutrition and Physical Activity,2009,6(1):21.
[6] Wolff-Hughes D L,Troiano R P, Boyer W R et al.Use of population-referenced total activity counts percentiles to assess and classify physical activity of population groups[J].Preventive Medicine, 2016, 87:35-40.
[7] Nguyen Q C,Kath S,Meng H W et al.Leveraging geotagged Twitter data to examine neighborhood happiness,diet,and physical activity[J]. Applied Geography,2016,73:77-88.
[8]齐兰兰,周素红.邻里建成环境对居民外出型休闲活动时空差异的影响:以广州市为例[J].地理科学, 2018, 38(1):31-40.[Qi Lanlan, Zhou Suhong. The influence of neighborhood built environments on the spatial-temporal characteristics of residents'daily leisure activities:A case study of Guangzhou. Scientia Geographica Sinica, 2018, 38(1):31-40.]
[9]李米环,李国强,江崇民.2013年南京、上海城区居民体力活动模式及其与超重/肥胖关系[J].卫生研究,2017,46(2):331-336.[Li Mihuan,Li Guoqiang,Jiang Chongmin.Physical activity patterns and their relationship with overweight/obesity in urban residents of Nanjing and Shanghai in 2013.Journal of Hygiene Research,2017,46(2):331-336.]
[10] Schuna J M, Johnson W D, Tudor-Locke C. Adult self-reported and objectively monitored physical activity and sedentary behavior:NHANES 2005-2006[J]. International Journal of Behavioral Nutrition and Physical Activity, 2013, 10(1):126.
[11] Juneau C E,Potvin L.Trends in leisure-,transport-,and work-related physical activity in Canada 1994-2005[J].Preventive Medicine,2010,51(5):384-386.
[12] Silva K S, Garcia L M T, Rabacow F M et al. Physical activity as part of daily living:Moving beyond quantitative recommendations[J]. Preventive Medicine, 2017, 96:160-162.
[13] Althoff T, Sosi?R, Hicks J L et al. Large-scale physical activity data reveal worldwide activity inequality[J]. Nature, 2017, 547(7663):336-339.
[14]张彦峰,江崇民,蔡睿,等.中国国民体力活动水平的区域特征研究[J].体育科学, 2012, 32(9):3-10, 22.[Zhang Yanfeng,Jiang Chongmin, Cai Rui et al. Regional characteristics of the national physical activity level in China. China Sport Science,2012, 32(9):3-10, 22.]
[15] Matisziw T C, Nilon C H, Wilhelm Stanis S A et al. The right space at the right time:The relationship between children's physical activity and land use/land cover[J]. Landscape and Urban Planning, 2016, 151:21-32.
[16] Hillsdon M, Coombes E, Griew P et al. An assessment of the relevance of the home neighbourhood for understanding environmental influences on physical activity:How far from home do people roam?[J]. International Journal of Behavioral Nutrition and Physical Activity, 2015, 12:100.
[17] Stewart T, Duncan S, Schipperijn J. Adolescents who engage in active school transport are also more active in other contexts:A space-time investigation[J]. Health&Place, 2017, 43:25-32.
[18]关美宝,郭文伯,柴彦威.人类移动性与健康研究中的时间问题[J].地理科学进展,2013,32(9):1344-1351.[Guan Meibao,Guo Wenbo,Chai Yanwei.Temporally integrated human mobility and health research.Progress in Geography,2013,32(9):1344-1351.]
[19] Hurvitz P M, Moudon A V, Kang B et al. How far from home?The locations of physical activity in an urban US setting[J]. Preventive Medicine, 2014, 69:181-186.
[20] Feuillet T, Charreire H, Menai M et al. Spatial heterogeneity of the relationships between environmental characteristics and active commuting:Towards a locally varying social ecological model[J]. International Journal of Health Geographics, 2015, 14:12.
[21] Feuillet T, Salze P, Charreire H et al. Built environment in local relation with walking:Why here and not there?[J]. Journal of Transport&Health, 2016, 3(4):500-512.
[22] Perchoux C, Kestens Y, Brondeel R et al. Accounting for the daily locations visited in the study of the built environment correlates of recreational walking(the RECORD Cohort Study)[J].Preventive Medicine, 2015, 81:142-149.
[23] Saarloos D, Kim J E, Timmermans H. The built environment and health:introducing individual space-time behavior[J]. International Journal of Environmental Research and Public Health,2009, 6(6):1724-1743.
[24] Chaix B, Méline J, Duncan S et al. Neighborhood environments, mobility, and health:Towards a new generation of studies in environmental health research[J]. Revue d'épidémiologie Et De SantéPublique, 2013, 61:S139-S145.
[25] MacIntyre S, Ellaway A, Cummins S. Place effects on health:How can we conceptualise, operationalise and measure them?[J]. Social Science&Medicine, 2002, 55(1):125-139.
[26] Perchoux C, Chaix B, Brondeel R et al. Residential buffer, perceived neighborhood, and individual activity space:New refinements in the definition of exposure areas—The RECORD Cohort Study[J]. Health&Place, 2016, 40:116-122.
[27] Trost S G,Owen N,Bauman A E et al.Correlates of adults'participation in physical activity:Review and update[J].Medicine&Science in Sports&Exercise,2002,34(12):1996-2001.
[28] Plotnikoff R C, Mayhew A, Birkett N et al. Age, gender, and urban-rural differences in the correlates of physical activity[J].Preventive Medicine, 2004, 39(6):1115-1125.
[29] Florindo A A, Guimar?es V V, Cesar C L G et al. Epidemiology of leisure, transportation, occupational, and household physical activity:Prevalence and associated factors[J]. Journal of Physical Activity and Health, 2009, 6(5):625-632.
[30] Tigbe W W, Lean M E J, Granat M H. A physically active occupation does not result in compensatory inactivity during out-of-work hours[J]. Preventive Medicine, 2011, 53(1/2):48-52.
[31] Ivory V C, Blakely T, Pearce J et al. Could strength of exposure to the residential neighbourhood modify associations between walkability and physical activity?[J]. Social Science&Medicine, 2015, 147:232-241.
[32] Stahl S T, Albert S M. Gender differences in physical activity patterns among older adults who fall[J]. Preventive Medicine,2015, 71:94-100.
[33] Cerin E, Mitá?J, Cain K L et al. Do associations between objectively-assessed physical activity and neighbourhood environment attributes vary by time of the day and day of the week?IPEN adult study[J]. International Journal of Behavioral Nutrition and Physical Activity, 2017, 14:34.
[34]南京日报.南京市2018年国民经济和社会发展统计公报[EB/OL].http://njrb.njdaily.cn/njrb/html/2019-04/01/content_532184.htm?div=2.2018-06-10.[The Nanjing Daily.Nanjing statistical bulletin on national economic and social development 2018.http://njrb.njdaily.cn/njrb/html/2019-04/01/content_532184.htm?div=2.2018-06-10.]
[35]南京市统计局.南京统计年鉴(2017)[M/OL]. http://221.226.86.104/file/nj2004/2017/index.htm.[Nanjing Statistical Bureau. Statistical yearbook of Nanjing(2017). http://221.226.
[36]南京市人民政府.南京市全民健身实施计划[EB/OL].http://www.nanjing.gov.cn/xxgk/szf/201701/t20170126_435 1268.html.2018-06-10.[The People's Government of Nanjing. Implementation plan of national fitness program in Nanjing. http://www.nj.gov.cn/xxgk/szf/201701/t20170126_4351267.html.2018-06-10.]
[37]南京市卫生和生育计划委员会.2017年南京市户籍居民病、伤死亡原因简析[EB/OL]. http://wjw.nanjing.gov.cn/njswshjhsywyh/201805/t20180504_5387258.html.2018-06-10.[The Municipal Health and Reproductive Planning Committee of Nanjing.Analysis on causes of death and injury of registered residents in Nanjing in 2017. http://wjw.nanjing.gov.cn/njswshjhsywyh/201805/t201-80504_5387258.html.2018-06-10.]
[38] Craig C, Marshall A, SJ?STR?M M et al. International physical activity questionnaire:12-country reliability and validity.Medicine&Science in Sports&Exercise, 2003, 35(8):1381-1395.86.104/file/nj2004/2017/index.htm.]
[39]陈春,塔吉努尔·海力力,陈勇.女性老年人肥胖的建成环境影响因素及规划响应研究[J].人文地理,2018,33(4):76-81.[Chen Chun,Hailili Tajnur, ChenYong. Built environment’s influence on obesity of the older women and its planning responses.Human Geography, 2018,33(4):76-81.]
[40]王晓娟.混合效应模型中的参数估计[D].杭州:浙江大学,2013.[Wang Xiaojuan.Parameter estimation in mixed effect models.Hangzhou:Zhejiang University, 2013.]
[41]郝静,孙成,郭兴宇,等.京津冀内陆平原区PM2.5浓度时空变化定量模拟[J].环境科学,2018,39(4):1455-1465.[Hao Jing,Sun Cheng,Guo Xingyu et al.Simulation of the spatio-temporally resolved PM2.5aerosol mass concentration over the inland plain of the Beijing-Tianjin-Hebei region. Environmental Science,2018,39(4):1455-1465.]
(1)根据南京统计年鉴(2017年)[35],2016年南京市三次产业占比(单位:%)为2.4∶39.2∶58.4,全市城镇非私营单位从业人员中从事服务业人员占比达到55.74%,推断出南京市就业结构以服务型职业为主。
(2)无重大疾病,行动方便且能够独立完成问卷调研的常住居民。
(3)假定每人每天至少有8 h睡眠时间,个体报告的全部身体活动每天累计时间总和则不能超过960 min。
(1)为减少原始数据因数值差异大带来的估计误差,对Y值进行标准化处理,即通过每一变量原值与其平均值之差除以该变量的标准差获取新值。
(2)1 000 m阈值选择主要考虑:一是在居民可接受的15 min步行范围内;二是与居民日常发生联系最多(如买菜、送小孩上下学、散步等)的日常生活空间范围。
(1)为解决解释变量和交互项共线性问题,对交互项变量做去中心化处理。在性别和其它变量交互分析中,以男性作为参照,分别测度女性样本和年龄、空间距离的交互作用。
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