云南不明原因猝死特征研究及病因探讨
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摘要
目的
自上世纪七十年代以来,云南省多个村庄陆续发生不明原因聚集性猝死事件,九十年代逐渐加重,而病因一直未明。为加强病因研究,2005年国家启动了攻关课题。2006年课题组发现猝死病例死前食用过一种学术上尚未命名的俗称小白菌的野生菌,之后又发现多例猝死病例死前食用过小白菌,动物试验和植物化学表明小白菌有毒性。同时也注意到部分猝死病例未发现食用小白菌,除小白菌外,还应存在其它致病因素。
2007年本人加入该项课题,主要任务是在前期研究的基础上继续开展病因探索,深入分析流行病及相关的自然生态特征,对比分析不同聚集性质的猝死病例发病特征,评估健康教育效果,了解猝死自然村超额死亡情况,2010年还与地质专家共同参与了两起猝死事件的调查,最终为进一步的病因研究和防控策略的制定提供依据和参考。
方法
1.整理1975-2009年猝死病例的流行病学资料和2005-2009年猝死病例的临床资料,描述云南不明原因猝死时空分布特征和临床特征；收集全国和云南省气温、降水和海拔资料,利用空间分析技术探索云南不明原因猝死发生地及发生时的自然生态特征,并探索性预测云南不明原因猝死的发病区域。
2.根据聚集性质的不同对猝死病例进行分类,比较不同类型猝死病例在流行病学、临床、生态、小白菌食用情况等方面的差异。
3.选择云南不明原因猝死发病形势相对较重的鹤庆、大姚、腾冲、祥云、凤庆、宁蒗六县进行现场健康教育评估,采用深入访谈、入户问卷调查和现场察看等方法了解健康教育开展情况；其余猝死区县,由各区县疾病预防控制中心自行组织有关人员填写调查问卷,以电子邮件形式返回。
4.选择云南不明原因猝死发病形势相对较重的大姚县石羊、鹤庆县中江、腾冲县界头、祥云县米甸四乡镇进行死因研究,通过回顾调查和死因监测的方法收集2004-2009年居民死因资料,比较猝死自然村(发生过云南不明原因猝死的自然村)和对照自然村(未发生过云南不明原因猝死的自然村)的全死因特征。
5.对2010年云南省内发生的猝死现场进行地质学调查,检测空气中二氧化碳、氧气等气体,回顾具有类似特征的既往猝死事件。
6.概括和总结云南不明原因猝死特征,形成云南不明原因猝死病因链假说。
结果
1.①1975-2009年云南省共有25个区县、105个自然村报告414例云南不明原因猝死病例,其中女性占61%。猝死发生日期中位数为7月23日,95%的猝死病例发生在6月18日到9月2日期间,一天中的8时和18时为发病高峰。②猝死自然村分布在云南省西北部的从腾冲县到宁蒗县之间的条状带上,以及云南省中部的一片区域；只有一年出现过猝死病例的自然村占72%(75/105)。③猝死发生前有降雨、升温现象。猝死病例数年度变化与年均气温年度变化呈正相关：猝死自然村发病时间(指一年内发生的早或迟)与海拔高度呈正相关,与年均气温呈负相关。除云南省外,根据气温、降水和海拔预测的发病区域还包括四川省南部和贵州省西北部的一小片区域。
2.猝死病例被分成家庭聚集性猝死病例(Ⅰ类)、村庄聚集性猝死病例(Ⅱ类)和散发猝死病例(Ⅲ类)三类,分别占总猝死病例的64.3%、23.7%和12.0%。Ⅰ类和Ⅲ类在一天中发病时刻有聚集性,Ⅱ类无聚集性。有Ⅰ类病例发生的事件,发病前降雨现象明显；有Ⅱ类病例发生的事件,发病前气温较高并有升温过程。Ⅰ-Ⅲ类发病到死亡间隔时间中位数分别为25分钟、5分钟和170分钟。Ⅰ类病例小白菌食用率为56%，Ⅱ和Ⅲ类病例均未食用过小白菌。
3.小白菌食用率由16.7%显著下降到3.8%。2006-2009年间总发病数43例明显较2002-2005年间的总病例数121例少；有7个自然村在2002-2005年间和2006-2009年间均发病,2006-2009年期间发病数为17例,也较2002-2005年间发病数28例少。
4.2004-2009年猝死自然村组粗死亡率为9.05‰(标化率6.84‰),去除云南不明原因猝死病例后粗死亡率为8.16‰(标化率5.74‰),均明显高于对照自然村组粗死亡率6.14‰(标化率4.79‰)。云南不明原因猝死粗死亡率为0.89‰,在死亡原因中排第4位。猝死自然村组死亡率比对照自然村组高2.91‰,其中呼吸系统类疾病高1.05‰,损伤和中毒外因原因类疾病高0.55‰,消化系统类疾病高0.32‰。除云南不明原因猝死外的其它类疾病高出部分合计为2.02‰,是云南不明原因猝死的2.3倍。
5.二氧化碳异常高达2490ppm,氧气异常低达7%。弥勒和既往发病的凤庆县均有随家庭地势升高发病日期延后的现象。
结论
1.云南不明原因猝死具有严格的夏季聚集性,早晚就餐时刻为发病高峰。发病区域具有确定性,主要位于云南省西北部和中部。但发病自然村具有相对不确定性,既有多年反复发病的少数特定自然村,又有不断出现的新发猝死自然村,发病一年后不再发病。气温、降雨和海拔为重要影响因素,预测出的云南不明原因猝死发病区域主要局限在云南省的西北部和中部以及与云南省接壤的四川省南部和贵州省西北部的小片区域。
2.家庭聚集性猝死病例和村庄聚集性猝死病例在发病特征方面存在明显的差异,可能是由不同的致病因素导致的。2006-2009年的流行病学资料支持小白菌学说解释家庭聚集性猝死病例。
3.针对小白菌的干预措施取得明显效果,小白菌食用率明显下降,云南不明原因猝死病例数减少。
4.猝死自然村除云南不明原因猝死引起的超额死亡外,还存在其它更加严重的超额死亡现象。
5.云南省内存在地气致人猝死的可能性,地气可能和云南不明原因猝死有关。
Objective
The Yunnan Unexplained Sudden Deaths (YUSD) have occurred in many villages in Yunnan Province since the1970's. The incidence gradually increased during the1990's, while the cause remained elusive. To identify the cause of YUSD, the Chinese National Ministry of Science and Technology and Ministry of Health jointly started a project in2005. In2006, some YUSD cases were found to have eaten a certain mushroom before illness onset. This particular mushroom had not been named; local villagers called it the "little white mushroom." After that, many YUSD cases were found to have eaten the mushroom. The results of animal experiments and plant chemistry analysis revealed that the little white mushroom was toxic. In addition to the little white mushroom, there had to be other unknown causes because some YUSD case-patients did not eat the mushroom.
The major tasks of this investigation were to further investigate the etiology of this disease, to more thoroughly explore its epidemiologic and ecological characteristics, to compare the characteristics between different clusters of YUSD cases, to evaluate the effectiveness of a health education campaign about YUSD, to study the excess deaths in villages where YUSD occurred, and to conduct a geological survey in the area where YUSD occurred with the assistance of a geologist. The ultimate purpose of the study was to provide more evidence and information for further research of the causes of YUSD and for formulating prevention and control strategies.
Methods
1. We collected epidemiologic data of YUSD cases during1975-2009and the clinical information of cases during2005-2009, and analyzed the temporal-spatial distribution and clinical characteristics of YUSD. We collected the meteorological and geographical data in China and in Yunnan Province, including temperature, precipitation, and elevation. We constructed a predictive model on the occurrence of YUSD by using spatial analysis techniques.
2. We classified YUSD cases by types of clusters, and compared different types of cases with respect to their epidemiologic, clinical, and ecological features and exposure history in relation to the little white mushroom.
3. We conducted a field evaluation of a health education campaign in Heqing, Dayao, Tengchong, Xiayun, Fengqing, and Ninglang counties. We performed in-person and questionnaire interviews, and conducted a field investigation to evaluate the health education campaign. In the other counties where YUSD had occurred, we used a questionnaires through e-mail to conduct the interviews.
4. We selected four townships with the most number of YUSD cases (i.e., Shiyang, Zhongjiang, Jietou and Midian townships), and collected data about causes of death during2004-2009using retrospective investigation and active surveillance. We compared the characteristics the decedents between villages where YUSD had occurred ("case group", YUSD villages) and villages where YUSD had not occurred ("control group").
5. We conducted a geological investigation in places where YUSD occurred during2010, and measured the concentration of various gases in the air, such as carbon dioxide, oxygen, and reviewed similar events from previous YUSD events.
6. We summarized the characteristics of YUSD and formed a hypothesis about the causal chain of YUSD.
Results
1.①In total,414YUSD cases (females:61%) were reported during1975-2009in105villages of25counties in Yunnan Province. The median calendar date of illness onset was July23;95%of the YUSD cases occurred between June18and September2. The peak hours of illness onset were at08:00and18:00hours.②Most of the YUSD villages were located on a belt extending from Tengchong county to Ninglang county in the northwestern part of Yunnan Province; a small number of the YUSD villages were located at the center of Yunnan Province. Villages where YUSD has occurred during one of those years accounted for72%(75/105).③Typically, before a YUSD case occurred, it was rainy and the temperature was relatively high. The annual number of cases positively correlated with the annual average temperature. Also, the higher the altitude was and the lower the annual average temperature was, the earlier was the occurrence of YUSD cases. In addition to Yunnan Province, our model predicted that similar sudden death cases could also occur in southern Sichuan Province and a small area in northwestern Guizhou Province, based on temperature, precipitation, and altitude data.
2. Approximately64%of the cases occurred as family clusters (Class Ⅰ),24%as village clusters (Class Ⅱ), and12%as non-clusters (Class Ⅲ). Class Ⅰ and Class Ⅲ(but not Class Ⅱ) cases also showed clustering by the hours of the day. Precipitation typically occurred before Class Ⅰ cases; whereas a high and rising temperature usually preceded Class Ⅱ cases. The median interval from onset to death was25m for Class Ⅰ cases,5m for Class Ⅱ cases, and170m for Class Ⅲ cases.56%of the Class Ⅰ cases had a history of consuming the little white mushroom, whereas none of the Class Ⅱ and Class Ⅲ cases had this history.
3. The proportion of village residents who consumed the little white mushroom decreased from16.7%to3.8%. The number of YUSD cases decreased from121during2002-2005to43during2006-2009. In7villages, YUSD occurred during2002-2005and2006-2009; in these7villages, the number of YUSD cases also decreased from28during2002-2005to17during2006-2009.
4. The total crude mortality rate was9.05‰(age-adjusted rate:6.84%o) in case group during2004-2009. The crude rate was8.16‰(age-adjusted rate:5.74‰) when YUSD cases were excluded. These rates were both higher than the rate of6.14‰(age-adjusted rate:4.79‰) in the control group. The mortality rate due to YUSD was0.89%o, which ranked fourth of all causes in the case group. The mortality rate in the case group was2.91%o in excess of control group. The excess mortality rate in the case-group was1.05%o for respiratory diseases,0.55%o for injure/poising diseases, and0.32%o for digestive diseases, compared to the control group. Excluding YUSD cases, the excess mortality due to other causes was2.02%o, which was2.3times as that of YUSD.
5. The concentrations of carbon dioxide was2490ppm, and oxygen in air was7%. In comparison, in Mile County and Fengqing County, the higher the altitude the later the occurrence of YUSD cases in a calendar year.
Conclusions
1. YUSD cases had strict seasonality in that they only occurred in the summer. The peak occurrence hours were at breakfast and dinner times. Cases were mainly located in the northwestern and central areas of Yunnan Province and had a clear boundary. However, the exact location for the YUSD cases was unpredictable. In some villages there were multiple occurrences of YUSD, whereas in other villages YUSD only occurred during one of the years during the study period. Temperature, precipitation and altitude were correlated with YUSD. Based on these factors, the predicted regions where YUSD could occur included the northwestern and central Yunnan Province and small regions in southern Sichuan Province and northwestern Guizhou Province.
2. Cases exhibiting family clustering and cases exhibiting village clustering had different characteristics. This finding might suggest different causative agents. The epidemiologic data of2006-2009supported the hypothesis that some family-clustering YUSD cases were caused by the little white mushroom.
3. Health education campaign about YUSD had achieved significant effects, as shown by the sharp reduction in the rate of the villagers consuming the little white mushrooms and the corresponding decline in the number of YUSD cases in recent years.
4. Villages where the YUSD occurred had a higher mortality rate than other villages. This excess mortality cannot be explained by YUSD alone.
5. The villages where YUSD occurred had abnormal measurements of geogas which may be causes of some YUSD cases.
自上世纪七十年代以来,云南省多个村庄陆续发生不明原因聚集性猝死事件,九十年代逐渐加重,而病因一直未明。为加强病因研究,2005年国家启动了攻关课题。2006年课题组发现猝死病例死前食用过一种学术上尚未命名的俗称小白菌的野生菌,之后又发现多例猝死病例死前食用过小白菌,动物试验和植物化学表明小白菌有毒性。同时也注意到部分猝死病例未发现食用小白菌,除小白菌外,还应存在其它致病因素。
2007年本人加入该项课题,主要任务是在前期研究的基础上继续开展病因探索,深入分析流行病及相关的自然生态特征,对比分析不同聚集性质的猝死病例发病特征,评估健康教育效果,了解猝死自然村超额死亡情况,2010年还与地质专家共同参与了两起猝死事件的调查,最终为进一步的病因研究和防控策略的制定提供依据和参考。
方法
1.整理1975-2009年猝死病例的流行病学资料和2005-2009年猝死病例的临床资料,描述云南不明原因猝死时空分布特征和临床特征；收集全国和云南省气温、降水和海拔资料,利用空间分析技术探索云南不明原因猝死发生地及发生时的自然生态特征,并探索性预测云南不明原因猝死的发病区域。
2.根据聚集性质的不同对猝死病例进行分类,比较不同类型猝死病例在流行病学、临床、生态、小白菌食用情况等方面的差异。
3.选择云南不明原因猝死发病形势相对较重的鹤庆、大姚、腾冲、祥云、凤庆、宁蒗六县进行现场健康教育评估,采用深入访谈、入户问卷调查和现场察看等方法了解健康教育开展情况；其余猝死区县,由各区县疾病预防控制中心自行组织有关人员填写调查问卷,以电子邮件形式返回。
4.选择云南不明原因猝死发病形势相对较重的大姚县石羊、鹤庆县中江、腾冲县界头、祥云县米甸四乡镇进行死因研究,通过回顾调查和死因监测的方法收集2004-2009年居民死因资料,比较猝死自然村(发生过云南不明原因猝死的自然村)和对照自然村(未发生过云南不明原因猝死的自然村)的全死因特征。
5.对2010年云南省内发生的猝死现场进行地质学调查,检测空气中二氧化碳、氧气等气体,回顾具有类似特征的既往猝死事件。
6.概括和总结云南不明原因猝死特征,形成云南不明原因猝死病因链假说。
结果
1.①1975-2009年云南省共有25个区县、105个自然村报告414例云南不明原因猝死病例,其中女性占61%。猝死发生日期中位数为7月23日,95%的猝死病例发生在6月18日到9月2日期间,一天中的8时和18时为发病高峰。②猝死自然村分布在云南省西北部的从腾冲县到宁蒗县之间的条状带上,以及云南省中部的一片区域；只有一年出现过猝死病例的自然村占72%(75/105)。③猝死发生前有降雨、升温现象。猝死病例数年度变化与年均气温年度变化呈正相关：猝死自然村发病时间(指一年内发生的早或迟)与海拔高度呈正相关,与年均气温呈负相关。除云南省外,根据气温、降水和海拔预测的发病区域还包括四川省南部和贵州省西北部的一小片区域。
2.猝死病例被分成家庭聚集性猝死病例(Ⅰ类)、村庄聚集性猝死病例(Ⅱ类)和散发猝死病例(Ⅲ类)三类,分别占总猝死病例的64.3%、23.7%和12.0%。Ⅰ类和Ⅲ类在一天中发病时刻有聚集性,Ⅱ类无聚集性。有Ⅰ类病例发生的事件,发病前降雨现象明显；有Ⅱ类病例发生的事件,发病前气温较高并有升温过程。Ⅰ-Ⅲ类发病到死亡间隔时间中位数分别为25分钟、5分钟和170分钟。Ⅰ类病例小白菌食用率为56%，Ⅱ和Ⅲ类病例均未食用过小白菌。
3.小白菌食用率由16.7%显著下降到3.8%。2006-2009年间总发病数43例明显较2002-2005年间的总病例数121例少；有7个自然村在2002-2005年间和2006-2009年间均发病,2006-2009年期间发病数为17例,也较2002-2005年间发病数28例少。
4.2004-2009年猝死自然村组粗死亡率为9.05‰(标化率6.84‰),去除云南不明原因猝死病例后粗死亡率为8.16‰(标化率5.74‰),均明显高于对照自然村组粗死亡率6.14‰(标化率4.79‰)。云南不明原因猝死粗死亡率为0.89‰,在死亡原因中排第4位。猝死自然村组死亡率比对照自然村组高2.91‰,其中呼吸系统类疾病高1.05‰,损伤和中毒外因原因类疾病高0.55‰,消化系统类疾病高0.32‰。除云南不明原因猝死外的其它类疾病高出部分合计为2.02‰,是云南不明原因猝死的2.3倍。
5.二氧化碳异常高达2490ppm,氧气异常低达7%。弥勒和既往发病的凤庆县均有随家庭地势升高发病日期延后的现象。
结论
1.云南不明原因猝死具有严格的夏季聚集性,早晚就餐时刻为发病高峰。发病区域具有确定性,主要位于云南省西北部和中部。但发病自然村具有相对不确定性,既有多年反复发病的少数特定自然村,又有不断出现的新发猝死自然村,发病一年后不再发病。气温、降雨和海拔为重要影响因素,预测出的云南不明原因猝死发病区域主要局限在云南省的西北部和中部以及与云南省接壤的四川省南部和贵州省西北部的小片区域。
2.家庭聚集性猝死病例和村庄聚集性猝死病例在发病特征方面存在明显的差异,可能是由不同的致病因素导致的。2006-2009年的流行病学资料支持小白菌学说解释家庭聚集性猝死病例。
3.针对小白菌的干预措施取得明显效果,小白菌食用率明显下降,云南不明原因猝死病例数减少。
4.猝死自然村除云南不明原因猝死引起的超额死亡外,还存在其它更加严重的超额死亡现象。
5.云南省内存在地气致人猝死的可能性,地气可能和云南不明原因猝死有关。
Objective
The Yunnan Unexplained Sudden Deaths (YUSD) have occurred in many villages in Yunnan Province since the1970's. The incidence gradually increased during the1990's, while the cause remained elusive. To identify the cause of YUSD, the Chinese National Ministry of Science and Technology and Ministry of Health jointly started a project in2005. In2006, some YUSD cases were found to have eaten a certain mushroom before illness onset. This particular mushroom had not been named; local villagers called it the "little white mushroom." After that, many YUSD cases were found to have eaten the mushroom. The results of animal experiments and plant chemistry analysis revealed that the little white mushroom was toxic. In addition to the little white mushroom, there had to be other unknown causes because some YUSD case-patients did not eat the mushroom.
The major tasks of this investigation were to further investigate the etiology of this disease, to more thoroughly explore its epidemiologic and ecological characteristics, to compare the characteristics between different clusters of YUSD cases, to evaluate the effectiveness of a health education campaign about YUSD, to study the excess deaths in villages where YUSD occurred, and to conduct a geological survey in the area where YUSD occurred with the assistance of a geologist. The ultimate purpose of the study was to provide more evidence and information for further research of the causes of YUSD and for formulating prevention and control strategies.
Methods
1. We collected epidemiologic data of YUSD cases during1975-2009and the clinical information of cases during2005-2009, and analyzed the temporal-spatial distribution and clinical characteristics of YUSD. We collected the meteorological and geographical data in China and in Yunnan Province, including temperature, precipitation, and elevation. We constructed a predictive model on the occurrence of YUSD by using spatial analysis techniques.
2. We classified YUSD cases by types of clusters, and compared different types of cases with respect to their epidemiologic, clinical, and ecological features and exposure history in relation to the little white mushroom.
3. We conducted a field evaluation of a health education campaign in Heqing, Dayao, Tengchong, Xiayun, Fengqing, and Ninglang counties. We performed in-person and questionnaire interviews, and conducted a field investigation to evaluate the health education campaign. In the other counties where YUSD had occurred, we used a questionnaires through e-mail to conduct the interviews.
4. We selected four townships with the most number of YUSD cases (i.e., Shiyang, Zhongjiang, Jietou and Midian townships), and collected data about causes of death during2004-2009using retrospective investigation and active surveillance. We compared the characteristics the decedents between villages where YUSD had occurred ("case group", YUSD villages) and villages where YUSD had not occurred ("control group").
5. We conducted a geological investigation in places where YUSD occurred during2010, and measured the concentration of various gases in the air, such as carbon dioxide, oxygen, and reviewed similar events from previous YUSD events.
6. We summarized the characteristics of YUSD and formed a hypothesis about the causal chain of YUSD.
Results
1.①In total,414YUSD cases (females:61%) were reported during1975-2009in105villages of25counties in Yunnan Province. The median calendar date of illness onset was July23;95%of the YUSD cases occurred between June18and September2. The peak hours of illness onset were at08:00and18:00hours.②Most of the YUSD villages were located on a belt extending from Tengchong county to Ninglang county in the northwestern part of Yunnan Province; a small number of the YUSD villages were located at the center of Yunnan Province. Villages where YUSD has occurred during one of those years accounted for72%(75/105).③Typically, before a YUSD case occurred, it was rainy and the temperature was relatively high. The annual number of cases positively correlated with the annual average temperature. Also, the higher the altitude was and the lower the annual average temperature was, the earlier was the occurrence of YUSD cases. In addition to Yunnan Province, our model predicted that similar sudden death cases could also occur in southern Sichuan Province and a small area in northwestern Guizhou Province, based on temperature, precipitation, and altitude data.
2. Approximately64%of the cases occurred as family clusters (Class Ⅰ),24%as village clusters (Class Ⅱ), and12%as non-clusters (Class Ⅲ). Class Ⅰ and Class Ⅲ(but not Class Ⅱ) cases also showed clustering by the hours of the day. Precipitation typically occurred before Class Ⅰ cases; whereas a high and rising temperature usually preceded Class Ⅱ cases. The median interval from onset to death was25m for Class Ⅰ cases,5m for Class Ⅱ cases, and170m for Class Ⅲ cases.56%of the Class Ⅰ cases had a history of consuming the little white mushroom, whereas none of the Class Ⅱ and Class Ⅲ cases had this history.
3. The proportion of village residents who consumed the little white mushroom decreased from16.7%to3.8%. The number of YUSD cases decreased from121during2002-2005to43during2006-2009. In7villages, YUSD occurred during2002-2005and2006-2009; in these7villages, the number of YUSD cases also decreased from28during2002-2005to17during2006-2009.
4. The total crude mortality rate was9.05‰(age-adjusted rate:6.84%o) in case group during2004-2009. The crude rate was8.16‰(age-adjusted rate:5.74‰) when YUSD cases were excluded. These rates were both higher than the rate of6.14‰(age-adjusted rate:4.79‰) in the control group. The mortality rate due to YUSD was0.89%o, which ranked fourth of all causes in the case group. The mortality rate in the case group was2.91%o in excess of control group. The excess mortality rate in the case-group was1.05%o for respiratory diseases,0.55%o for injure/poising diseases, and0.32%o for digestive diseases, compared to the control group. Excluding YUSD cases, the excess mortality due to other causes was2.02%o, which was2.3times as that of YUSD.
5. The concentrations of carbon dioxide was2490ppm, and oxygen in air was7%. In comparison, in Mile County and Fengqing County, the higher the altitude the later the occurrence of YUSD cases in a calendar year.
Conclusions
1. YUSD cases had strict seasonality in that they only occurred in the summer. The peak occurrence hours were at breakfast and dinner times. Cases were mainly located in the northwestern and central areas of Yunnan Province and had a clear boundary. However, the exact location for the YUSD cases was unpredictable. In some villages there were multiple occurrences of YUSD, whereas in other villages YUSD only occurred during one of the years during the study period. Temperature, precipitation and altitude were correlated with YUSD. Based on these factors, the predicted regions where YUSD could occur included the northwestern and central Yunnan Province and small regions in southern Sichuan Province and northwestern Guizhou Province.
2. Cases exhibiting family clustering and cases exhibiting village clustering had different characteristics. This finding might suggest different causative agents. The epidemiologic data of2006-2009supported the hypothesis that some family-clustering YUSD cases were caused by the little white mushroom.
3. Health education campaign about YUSD had achieved significant effects, as shown by the sharp reduction in the rate of the villagers consuming the little white mushrooms and the corresponding decline in the number of YUSD cases in recent years.
4. Villages where the YUSD occurred had a higher mortality rate than other villages. This excess mortality cannot be explained by YUSD alone.
5. The villages where YUSD occurred had abnormal measurements of geogas which may be causes of some YUSD cases.
引文
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[21]何英,李丽,吴巩胜,等.气候要素空间插值技术的研究进展.科协论坛(下半月),2010,3：59-61.
[22]彭红兰,刘芳,朵海瑞,等.三江源地区温度和降水量空间插值方法比较.安徽农业科学,2010,38(18)：9646-9649,9680.
[23]http://www.ynszxc.gov.cn/szxc/ProvincePage/default.aspx
[24]金丕焕,陈峰.医用统计方法(第三版).复旦大学出版社,2009.
[25]陈竺主编.全国第三次死因回顾抽样调查报告[M].北京：中国协和医科大学出版社,2008.
[26]http://news.sohu.com/20100903/n274678184.shtml
[27]严牛布,赵兴平,曹必武.一起不明原因村民死亡调查.现代预防医学,2006,33(12)：2457.
[28]申涛,施国庆,黄文丽,等.云南省35个村不明原因猝死发病特征分析.中国公共卫生,2010,26(2)：237-239.
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[2]张健,施国庆,黄文丽,等.云南七个家庭不明原因猝死的临床研究.中华心血管病杂志,2008,36(7)：613-617.
[3]杨林,黄文丽,李兆祥,等.1975-2004年云南不明原因心源性猝死.预防医学情报杂志,2008,24(2)：110-113.
[4]宋来凤,王红月,赵红.对云南“聚集性猝死”的一些病理学思考.中国循环杂志,2006,21：519-520
[5]黄文丽,杨林,赵溯,等.1978-2004年云南地方性暴发性心肌炎流行病学调查分析.地方病通报,2006,21(2)：23-25.
[6]施国庆,张健,黄文丽,等.云南省116例不明原因猝死回顾性研究.中华流行病学杂志,2006,27(2)：96-101.
[7]任金马,赵艳荣,黄文丽,等.2005年云南不明原因猝死的家庭和村庄聚集性研究.中华预防医学杂志,2007,41：143-145.
[8]王红月,赵红,宋来凤,等.29例云南不明原因聚集性猝死的尸检病理学研究.中华医学杂志,2007,87(31)：2209-2214.
[9]王红月,黄文丽,杨崇福,等.云南不明原因聚集性猝死中心肌炎病例的病理特点分析.中华病理学杂志,2007,36(12)：805-809.
[10]刘孝柏,宋先毅,刘继海,等.7例致心律失常性右室心肌病猝死病例流行病学调查报告.中华医学会第一次全国公共卫生学术会议论文集,2009.
[11]牛存龙,杨崇福,于维汉.云南爆发性病毒性心肌炎.中国地方病学杂志,2003,22(7)：40-45.
[12]杨林,黄文丽,李兆祥,等.云南地方性暴发性心肌炎临床特点分析.地方病通报,2006,21(5)：4-6.
[13]杨崇福,牛存龙,陈耀宗,等.楚雄州暴性性心肌炎发病与降水关系分析.中国地方病防治杂志,2003,18(1)：42-44.
[14]张福新.云南省丽江市历年不明原因心源性猝死病流行因素探讨.国外医学医学地理分册,2009,30(4)：183-184,199.
[15]侯龙才,邓世全,孟晓林,等.云南省鹤庆县中江阿拉禾村居民猝死病因调查.中国地方病学杂志,2002,21(3)：192-193.
[16]王跃兵,黄文丽,施国庆,等.云南省祥云县不明原因心源性猝死回顾性调查.中国地方病学杂志,2007,26(4)：425-427.
[17]http://cdc.cma.gov.cn
[18]http://srtm.csi.cgiar.org/selection/inputcoord.asp
[19]王劲峰,廖一兰,刘鑫.空间数据分析教程.北京：科学出版社,2010.
[20]刘湘南,黄方,王平,等.GIS空间分析原理与方法.北京：科学出版社,2006.
[21]何英,李丽,吴巩胜,等.气候要素空间插值技术的研究进展.科协论坛(下半月),2010,3：59-61.
[22]彭红兰,刘芳,朵海瑞,等.三江源地区温度和降水量空间插值方法比较.安徽农业科学,2010,38(18)：9646-9649,9680.
[23]http://www.ynszxc.gov.cn/szxc/ProvincePage/default.aspx
[24]金丕焕,陈峰.医用统计方法(第三版).复旦大学出版社,2009.
[25]陈竺主编.全国第三次死因回顾抽样调查报告[M].北京：中国协和医科大学出版社,2008.
[26]http://news.sohu.com/20100903/n274678184.shtml
[27]严牛布,赵兴平,曹必武.一起不明原因村民死亡调查.现代预防医学,2006,33(12)：2457.
[28]申涛,施国庆,黄文丽,等.云南省35个村不明原因猝死发病特征分析.中国公共卫生,2010,26(2)：237-239.
[1]Lawson AB. Statistical methods in spatial epidemiology (2nd ed)[M]. New York:John Wiley & Sons, 2006,111-115.
[2]Xu J. Application of national disease surveillance reporting system in early detection of infectious disease outbreaks[J]. Disease survillance,2006,21(4):212-216. (in Chinese)徐健.网络直报系统在早期发现传染病暴发中的应用[J].疾病监测,2006,21(4)：212-216
[3]Pfeiffer DU, Robinson TP, Stevenson M, et al. Spatial analysis in epidemiology[M]. Oxford:Oxford University Press,2008,17-66
[4]Peter A. Rogerson. Statistical methods for the detection of spatial clustering in case-control data[J]. Statistics in medicine,2006,25:811-823.
[5]Zhou XL, Wang XH, Yang K. Spatial epidemiology[M]. BeiJing:Science and Technology Press, 2009,47-49. (in Chinese)周晓农,王显红,杨坤等.空间流行病学[M].北京：科技出版社,2009.
[6]Wang JF. Spatial analysis[M]. BeiJing:Science and Technology Press,2006:57. (in Chinese)王劲峰等.空间分析[M].北京：科技出版社,2006.
[7]David WS Wong, Jay Lee. Statistical analysis of geographic information with Arcview GIS and ArcGIS[M]. New York:John Wiley & Sons,2005.
[8]Illian J, Penttinen A, Stoyan H, et al. Statistical analysis and modeling of spatial point patterns[M]. New York:John Wiley & Sons,2008.
[9]Cuzick J, Edwards R. Spatial clustering for inhomogeneous populations[J]. J Royal Statist Soc Series B,1990,52:73-104.
[10]Changhong Song, Martin Kulldorff. Likelihood based tests for spatial randomness[J]. Statist Med, 2006,25:825-839.
[11]Kulldorff M, Nagarwalla N. Spatial disease clusters:detection and inference[J]. Statist Med,1995, 14:799-810.
[12]Yiannakoulias N. Using population attributable risk to understand geographic disease clusters[J]. Health & Place,2009,15:1142-1148.
[13]Toshiro Tango. Statistical methods for disease clustering[M]. New York:Springer,2010,119-121
[14]Turnbull BW, Iwano EJ, Burnett WS, et al. Monitoring for clusters of disease:Applications to leukemia incidence in upstate New York[J]. Am. J. Epidemiol,1990,132:136-143.
[15]Huang L, Pickle LW, Das B. Evaluating spatial methods for investigating global clustering and cluster detection of cancer cases[J]. Statist Med,2008,27(25):5111-5142.
[16]Kulldorff M, Huang L, Pickle L, et al. An elliptic spatial scan statistic[J], Statist Med,2006, 25:3929-3943.
[17]Patil GP, Taillie C. Upper level set scan statistic for detecting arbitrarily shaped hotspots[J]. Environmental and Ecological Statistics,2004,11:183-197.
[18]Duczmal L, Assuncao R. A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters[J]. Computat Statist Data Anal,2004,45:269-286.
[19]Tango T, Takahashi K. A flexibly shaped spatial scan statistic for detecting clusters[J]. Inter J Health Geograph,2005,4,11.
[20]Michelozzi P, Capon A, Kirchmayer U, et al. Adult and Childhood Leukemia near a High-Power Radio Station in Rome, Italy. Am J Epidemiol,2002,155:1096-1103
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