中国居民食源性疾病的地理分布及影响因素分析

doi:10.3969/j.issn.1004-9479.2020.01.2018432

摘要/Abstract

摘要：

基于2012—2017年全国《中国卫生和计划生育统计年鉴》数据，采用空间自相关分析等方法，刻画中国居民食源性疾病的空间分布格局及其变化，并采用空间滞后面板回归模型（SLM）和时空地理加权模型（GTWR），识别影响食源性疾病空间分布的主要因素及其变化。结果表明：（1）中国食源性疾病分布具有不均衡性，总体趋势为集中分布于南部以及沿海地区，五年间集中区已出现明显的向北移动的趋势；（2）中国食源性疾病事件数具有一定的空间集聚特征，五年间空间集聚下降。高-高类型区主要分布于西南地区，而低-低类型区集中分布于中国北部。2011—2016年，中国食源性疾病变化趋势与空间分布特征类似；（3）空间滞后面板回归模型分析结果表明，食源性疾病事件具有显著的空间溢出效应。人口密度、突发环境事故的增加将使得食源性疾病增加，而政府财政投入、居民教育水平、城镇化、环境质量的提高将使得食源性疾病减少。除居民教育水平外其余变量也均具有显著的空间溢出效应；（4）时空地理加权模型分析结果表明，食源性疾病的影响因素存在空间差异。地区人口密度对食源性疾病的相对压力由东向西加大。政府财政投入对食源性疾病的降低作用由东南部沿海地区向其余地区递减。居民教育水平提高对食源性疾病降低作用由中部向东西逐步加大。城镇化率对食源性疾病降低作用由东南部沿海地区向其余地区递减。环境质量对食源性疾病降低作用由东南部沿海地区向其余地区递增；突发环境事故对食源性疾病的相对压力由中部向东西加大；年平均气温对食源性疾病的相对压力由南向北减小；年平均降雨量对食源性疾病的相对压力由东部沿海地区向西部内陆地区减小。

关键词: 食源性疾病, 地理分布, 影响因素, 中国, 空间回归模型, 时空地理加权模型

Abstract:

Based on the 2012-2017 China health and family planning statistics yearbook ,this article study the spatial pattern evolvement of the distribution of foodborne illness in China and its influence mechanism by applying SLM and GTWR models. The result shows that: 1)The distribution of foodborne diseases in China is unbalanced, and the overall trend is concentrated in the south and coastal areas. In the five years, there has been a significant trend of northward movement in concentrated areas; 2) The distribution of foodborne illness in China has a certain spatial agglomeration feature, but the space agglomeration has decreased in five years. The high- high type area is mainly distributed in the southwest region, while the low-low type regions are concentrated in northern China. From 2011 to 2016, the trend of the change of foodborne diseases in China is similar to that of spatial distribution. 3)SLM model shows that foodborne disease events have significant spatial spillover effects. The increase of population density, emergency environmental accidents will make foodborne disease increased, and the government financial input, residents education level, urbanization and the improvement of environment quality will reduce foodborne disease. In addition to the resident education, the remaining variables also have significant spatial spillover effects. 4)GTWR model shows that there are spatial differences in the influence factors of foodborne diseases. The relative pressure of population density on foodborne diseases increased from east to west. The effect of government financial input on foodborne diseases is decreasing from the southeast coast to the rest. Residents education level increased the role of foodborne disease reduction from central to east-west gradually. The effect of urbanization rate on foodborne diseases decreases from the southeast coast to the rest. The effect of environmental quality on foodborne diseases increases from the southeast coast to the rest. The relative pressure of sudden environmental accidents on foodborne diseases increases from middle to east. The effect of average annual temperature on foodborne diseases decreases from the south to the north. The effect of average annual precipitation on foodborne diseases decreases from the southeast coast to the rest.

Key words: foodborne illness, geographical distribution, influence mechanism, China, spatial regression model, geographical spatiotemporal weighted model

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.

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.

图/表 7

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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	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

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