深圳市盐田区2017年跌倒/坠落伤害病例特征与空间聚集性
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摘要
目的分析2017年深圳市盐田区跌倒/坠落伤害病例分布特征,探索其空间聚集性。方法描述性分析2017年盐田区跌倒/坠落病例特征,应用Arcgis 10.2绘制跌倒/坠落病例专题地图,利用Geoda 1.12进行跌倒/坠落的全局、局域空间自相关分析。结果 2017年深圳市盐田区跌倒/坠落病例共报告4 622例,占全部伤害病例28.91%;主要发生年龄段为0～15岁,占比37.19%。男女性别比1.97∶1,60岁以上女性病例数多于男性;冬季高发(28.66%);发生地点主要为家中(28.10%);伤害性质主要为挫伤/擦伤(48.27%);伤害严重程度以轻度(76.66%)为主;跌倒/坠落主要发生在明珠、永安、东海、大梅沙社区。全局自相关分析显示Moran’s I统计量为0.51,Z=3.29(P=0.004),说明盐田区跌倒/坠落的发生存在空间聚集性;局域自相关分析发现永安、明珠、东海和田东4个社区存在高属性值聚集(P=0.003),即跌倒/坠落发生的"热点"区域。结论深圳市盐田区儿童与老年女性是跌倒/坠落的重点预防人群,跌倒/坠落空间分布存在明显的空间聚集性。
Objective To investigate the distribution characteristics and spatial clusters of Falls in Yantian Distric of Shenzhen in 2017. Methods Descriptive analysis of the characteristics of Falls in Yantian District in 2017 was carried out, Arcgis 10.2 software was used to make thematic maps of Falls, Geoda l1.12 software was used to analyse the global spatial autocorrelation and local spatial autocorrelation of Falls. Results A total of 4 622 Falls cases were reported in Yantian Distric of Shenzhen City in 2017, accounting for 28.91% of all the injuries; the main age group was 0-15 years old, accounting for 37.19%. The sex ratio was 1.97:1. The number of female patients over 60 years old was higher than male cases. Most Falls occurred in winter(28.66%). The place of occurrence mainly was at home(28.10%); the nature of injury mainly was contusion/abrasion(48.27%); the severity of injury mainly was mild(76.66%); Falls mainly occurred in Mingzhu,Yongan,Donghai and Dameisha communities. Global spatial autocorrelation showed that there was a spatial aggregation in the occurrence of Falls in Yantian Distric(Moran's I=0.51, Z=3.29, P=0.004); Local spatial autocorrelation analysis found that there were high attribute value aggregations in four communities: Yongan, Mingzhu, Donghai and Tiandong(P=0.003), which were the ‘Hot spot' areas where Falls occurred. Conclusions Children and elderly women in Yantian District of Shenzhen were the key prevention population for Falls which clustered geographically.
Objective To investigate the distribution characteristics and spatial clusters of Falls in Yantian Distric of Shenzhen in 2017. Methods Descriptive analysis of the characteristics of Falls in Yantian District in 2017 was carried out, Arcgis 10.2 software was used to make thematic maps of Falls, Geoda l1.12 software was used to analyse the global spatial autocorrelation and local spatial autocorrelation of Falls. Results A total of 4 622 Falls cases were reported in Yantian Distric of Shenzhen City in 2017, accounting for 28.91% of all the injuries; the main age group was 0-15 years old, accounting for 37.19%. The sex ratio was 1.97:1. The number of female patients over 60 years old was higher than male cases. Most Falls occurred in winter(28.66%). The place of occurrence mainly was at home(28.10%); the nature of injury mainly was contusion/abrasion(48.27%); the severity of injury mainly was mild(76.66%); Falls mainly occurred in Mingzhu,Yongan,Donghai and Dameisha communities. Global spatial autocorrelation showed that there was a spatial aggregation in the occurrence of Falls in Yantian Distric(Moran's I=0.51, Z=3.29, P=0.004); Local spatial autocorrelation analysis found that there were high attribute value aggregations in four communities: Yongan, Mingzhu, Donghai and Tiandong(P=0.003), which were the ‘Hot spot' areas where Falls occurred. Conclusions Children and elderly women in Yantian District of Shenzhen were the key prevention population for Falls which clustered geographically.
引文
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[4] Dai D,Zhang YZ,Lynch CA,et al.Childhood drowning in Georgia:A geographic information system analysis [J].Appl Geogr,2013,37(2):11-22.DOI:10.1016/j.apgeog.2012.10.006.
[5] 马永成,王兆芬,李斌,等.基于GIS的青海省结核病时空分布特征研究 [J].中华疾病控制杂志,2018,22(4):340-344,353.DOI:10.16462/j.cnki.zhjhkz.2018.04.005.Ma YC,Wang ZF,Liu B,et al.Temporal and spatial distribution of tuberculosis in Qinghai Province based on GIS [J].Chin J Dis Control Prev,2018,22(4):340-344,353.DOI:10.16462/j.cnki.zhjhkz.2018.04.005.
[6] 何慧敏,杨莉,黄开勇.桂林市道路交通伤害的GIS空间分析 [J].中华疾病控制杂志,2012,16(11):995-997.He HM,Yang L,Huang KY.GIS spatial analysis on road traffic injuries in Guilin City [J].Chin J Dis Control Prev,2012,16(11):995-997.
[7] 田小草,汪韶洁,翟耀明,等.青岛市2010-2011年跌倒/坠落伤害的流行病学特征分析 [J].中华疾病控制杂志,2013,17(10):883-884.Tian XC,Wang YJ,Zhai YM,et al.Analysis on epidemiological features of the falls in Qingdao City,2010-2011 [J].Chin J Dis Control Prev,2013,17(10):833-884.
[8] 廖英,王玉林,刘华章,等.2014-2016年广州市老年人跌倒/坠落伤害特征及其影响因素分析 [J].中华疾病控制杂志,2018,22(2):117-121.DOI:10.16462/j.nki.zhjbkz.2018.02.004.Liao Y,Wang YL,Liu HZ,et al.Characteristics of unintentional fall-related injuries and the related factors among the elderly in Guangzhou from 2014 to 2016 [J].Chin J Dis Control Prev,2018,22(2):117-121.DOI:10.16462/j.nki.zhjbkz.2018.02.004.
[9] 周明.骨骼肌质量、肌力和功能性活动测试在肌少症和跌倒中的筛查研究 [D].北京:中国人民解放军医学院,2014.Zhou M.The study of skeletal muscle mass、muscle strength and physical function tests for screening of sarcopenia and fall [D].Beijing:The general hospital of the people’s liberation army,2014.
[10] 耳玉亮,段蕾蕾,叶鹏鹏,等.2014年全国伤害监测系统老年跌倒/坠落病例特征分析 [J].中华流行病学杂志,2016,37(1):24-28.DOI:10.3760/cma.j.issn.0254-6450.2016.01.005.Er YL,Duan LL,Ye PP,et al.Epidemiologic characteristics of fall in old population:Results from national injury surveillance in China,2014 [J].Chin J Epidemiol,2016,37(1):24-28.DOI:10.3760/cma.j.issn.0254-6450.2016.01.005.