World Regional Studies ›› 2020, Vol. 29 ›› Issue (1): 168-180.DOI: 10.3969/j.issn.1004-9479.2020.01.2018432
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Ruoyu WANG(), Baishi HUANG, Zhuolin PAN, Ye LIU()
Received:
2018-09-26
Revised:
2018-12-13
Online:
2020-01-20
Published:
2022-01-22
Contact:
Ye LIU
通讯作者:
刘晔
作者简介:
王若宇(1994-),男,博士研究生,主要研究方向为城市地理,E-mail:wangry6@mail2.sysu.edu.cn。
基金资助:
Ruoyu WANG, Baishi HUANG, Zhuolin PAN, Ye LIU. Spatial pattern evolvement of the distribution offoodborne illness in China and its influence mechanism[J]. World Regional Studies, 2020, 29(1): 168-180.
王若宇, 黄柏石, 潘卓林, 刘晔. 中国居民食源性疾病的地理分布及影响因素分析[J]. 世界地理研究, 2020, 29(1): 168-180.
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URL: https://sjdlyj.ecnu.edu.cn/EN/10.3969/j.issn.1004-9479.2020.01.2018432
变量 | 符号 | 样本量 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|---|
食源性疾病事件数(对数) | logcase | 180 | 3.418 | 1.173 | 0.000 | 6.554 |
人口密度(对数)/(人/平方公里) | logpop | 180 | 5.464 | 1.256 | 2.099 | 8.023 |
人均政府财政投入(对数)/(元/人) | logpubexpend | 180 | 7.145 | 0.354 | 6.402 | 8.155 |
地方大专及以上文化程度人口数占地区人口比率 | edu | 180 | 0.120 | 0.064 | 0.049 | 0.423 |
城镇化率 | urban | 180 | 56.003 | 12.606 | 34.960 | 89.600 |
环境质量指数 | environment | 180 | 0.654 | 0.139 | 0.195 | 0.850 |
突发环境事故数(对数) | logaccident | 180 | 2.138 | 1.112 | 0.000 | 5.529 |
年平均气温/摄氏度 | temp | 180 | 14.439 | 5.081 | 4.300 | 25.300 |
年平均降水(对数)/毫米 | logprecipitation | 180 | 958.983 | 0.655 | 5.003 | 7.986 |
Tab.1 Statistics of variables
变量 | 符号 | 样本量 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|---|
食源性疾病事件数(对数) | logcase | 180 | 3.418 | 1.173 | 0.000 | 6.554 |
人口密度(对数)/(人/平方公里) | logpop | 180 | 5.464 | 1.256 | 2.099 | 8.023 |
人均政府财政投入(对数)/(元/人) | logpubexpend | 180 | 7.145 | 0.354 | 6.402 | 8.155 |
地方大专及以上文化程度人口数占地区人口比率 | edu | 180 | 0.120 | 0.064 | 0.049 | 0.423 |
城镇化率 | urban | 180 | 56.003 | 12.606 | 34.960 | 89.600 |
环境质量指数 | environment | 180 | 0.654 | 0.139 | 0.195 | 0.850 |
突发环境事故数(对数) | logaccident | 180 | 2.138 | 1.112 | 0.000 | 5.529 |
年平均气温/摄氏度 | temp | 180 | 14.439 | 5.081 | 4.300 | 25.300 |
年平均降水(对数)/毫米 | logprecipitation | 180 | 958.983 | 0.655 | 5.003 | 7.986 |
变量 | 系数 | 标准差 |
---|---|---|
logpop | 2.764** | 1.142 |
logpubexpend | -0.432** | 0.207 |
edu | -2.938** | 1.488 |
urban | -0.211*** | 0.038 |
environment | -3.047** | 1.459 |
logaccident | 0.148*** | 0.052 |
temp | 0.004* | 0.003 |
logprecipitation | 0.124* | 0.065 |
W*logfood | 0.036** | 0.119 |
Tab.2 Parameter estimate of SLM
变量 | 系数 | 标准差 |
---|---|---|
logpop | 2.764** | 1.142 |
logpubexpend | -0.432** | 0.207 |
edu | -2.938** | 1.488 |
urban | -0.211*** | 0.038 |
environment | -3.047** | 1.459 |
logaccident | 0.148*** | 0.052 |
temp | 0.004* | 0.003 |
logprecipitation | 0.124* | 0.065 |
W*logfood | 0.036** | 0.119 |
变量 | 直接效应 | 标准差 | 间接效应 | 标准差 |
---|---|---|---|---|
logpop | 2.180** | 1.092 | 0.499** | 0.236 |
logpubexpend | -1.004** | 0.504 | 0.546** | 0.258 |
edu | -2.059** | 1.275 | -0.745 | 0.723 |
urban | -0.209*** | 0.036 | -0.008** | 0.004 |
environment | -3.167** | 1.467 | -0.121** | 0.056 |
logaccident | 0.128*** | 0.037 | 0.006** | 0.003 |
temp | 0.002** | 0.001 | 0.001 | 0.001 |
loglogprecipitation | 0.006** | 0.003 | 0.005 | 0.004 |
W*logfood | 0.036** | 0.119 |
Tab.3 SLM’s direct and indirect effect estimate results of econometric model
变量 | 直接效应 | 标准差 | 间接效应 | 标准差 |
---|---|---|---|---|
logpop | 2.180** | 1.092 | 0.499** | 0.236 |
logpubexpend | -1.004** | 0.504 | 0.546** | 0.258 |
edu | -2.059** | 1.275 | -0.745 | 0.723 |
urban | -0.209*** | 0.036 | -0.008** | 0.004 |
environment | -3.167** | 1.467 | -0.121** | 0.056 |
logaccident | 0.128*** | 0.037 | 0.006** | 0.003 |
temp | 0.002** | 0.001 | 0.001 | 0.001 |
loglogprecipitation | 0.006** | 0.003 | 0.005 | 0.004 |
W*logfood | 0.036** | 0.119 |
变量 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|
logpop | 0.776 | 0.567 | 0.005 | 2.264 |
logpubexpend | -3.094 | 1.603 | -5.646 | -0.434 |
edu | -14.390 | 8.463 | -38.520 | -2.243 |
urban | -0.073 | 0.051 | -0.192 | -0.009 |
environment | -1.972 | 1.753 | -6.323 | -0.074 |
logaccident | 0.221 | 0.152 | 0.019 | 0.711 |
temp | 0.180 | 0.103 | 0.011 | 0.399 |
loglogprecipitation | 0.689 | 0.414 | 0.062 | 1.689 |
Tab.4 GTWR estimate results of econometric model in 2016
变量 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|
logpop | 0.776 | 0.567 | 0.005 | 2.264 |
logpubexpend | -3.094 | 1.603 | -5.646 | -0.434 |
edu | -14.390 | 8.463 | -38.520 | -2.243 |
urban | -0.073 | 0.051 | -0.192 | -0.009 |
environment | -1.972 | 1.753 | -6.323 | -0.074 |
logaccident | 0.221 | 0.152 | 0.019 | 0.711 |
temp | 0.180 | 0.103 | 0.011 | 0.399 |
loglogprecipitation | 0.689 | 0.414 | 0.062 | 1.689 |
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