Payments for Ecosystem Services(PES)programs have been implemented in both developing and developed countries to conserve ecosystems and the vital services they provide.These programs also often seek to maintain or im...Payments for Ecosystem Services(PES)programs have been implemented in both developing and developed countries to conserve ecosystems and the vital services they provide.These programs also often seek to maintain or improve the economic wellbeing of the populations living in the corresponding(usually rural)areas.Previous studies suggest that PES policy design,presence or absence of concurrent PES programs,and a variety of socioeconomic and demographic factors can influence decisions of households to participate or not in the PES program.However,neighborhood impacts on household participation in PES have rarely been addressed.This study explores potential neighborhood effects on villagers'enrollment in the Grain-to-Green Program(GTGP),one of the largest PES programs in the world,using data from China's Fanjingshan National Nature Reserve.We utilize a fixed effects logistic regression model in combination with the eigenvector spatial filtering(ESF)method to explore whether neighborhood size affects household enrollment in GTGP.By comparing the results with and without ESF,we find that the ESF method can help account for spatial autocorrelation properly and reveal neighborhood impacts that are otherwise hidden,including the effects of area of forest enrolled in a concurrent PES program,gender and household size.The method can thus uncover mechanisms previously undetected due to not taking into account neighborhood impacts and thus provides an additional way to account for neighborhood impacts in PES programs and other studies.展开更多
目的分析急诊患者放弃有创抢救的原因并提出对策。方法选择2014年1月至2014年12月收入北京协和医院急诊抢救室的2673例患者，分为抢救组和放弃抢救组，对两组患者的基本情况、基础疾病、医疗费用支付方式、签署意见书的人员构成、患者...目的分析急诊患者放弃有创抢救的原因并提出对策。方法选择2014年1月至2014年12月收入北京协和医院急诊抢救室的2673例患者，分为抢救组和放弃抢救组，对两组患者的基本情况、基础疾病、医疗费用支付方式、签署意见书的人员构成、患者的治疗情况以及预后进行分析。结果两组患者男女性别构成差异无统计学意义（x^2=1．86，P=0．173）；放弃抢救组患者年龄明显高于抢救组患者（69．5±12．5 vs．58．6±19．2岁，F=28．92，P=0．000）；放弃抢救组中北京以外的患者比例更高（51．90％ vs 44．01％，x^2=10．59，P=0．001）；放弃抢救组中患慢性心衰、慢性呼吸衰竭、慢性肝性脑病、慢性肾衰竭、恶性肿瘤等慢性疾病的比例更高（8．17％ vs ．3．03％，8．17％ vs ．2．61％，3．80％ vs ．1．16％，5．32％ vs．1．44％，11．98％ vs．2．28％，均P=0．000）；放弃抢救组中白费患者比例更高（52．09％vs．41．08％，x^2=20．87，P=0．000）；在签署意见书的人员构成方面，由患者本人签署的放弃抢救的比例明显高于同意抢救（3．04％ vs．0．42％，x^2=64．40，P=0．000），而患者的子女、配偶、父母、兄弟姐妹以及其他人员签署的同意抢救和放弃抢救的比例差异无统计学意义；Logistic回归分析结果显示患者高龄、非北京患者、患慢性基础病、自费、由患者本人签署意见书是放弃有创抢救的重要影响因素；放弃抢救组患者的病死率明显高于抢救组（19．39％ vs．7．68％，x^2=64．40，P=0．000）。结论放弃有创抢救治疗的患者多为高龄或属于慢性疾病终末期，急诊医务人员应继续关注这些患者，采用无创的手段进行治疗或减轻患者的痛苦。展开更多
基金National Science Foundation under the Dynamics of Coupled Natural and Human Systems Program,No.DEB-1212183,No.BCS-1826839Financial and Research Support from San Diego State University,Population Research Infrastructure Program,No.P2C,No.HD050924。
文摘Payments for Ecosystem Services(PES)programs have been implemented in both developing and developed countries to conserve ecosystems and the vital services they provide.These programs also often seek to maintain or improve the economic wellbeing of the populations living in the corresponding(usually rural)areas.Previous studies suggest that PES policy design,presence or absence of concurrent PES programs,and a variety of socioeconomic and demographic factors can influence decisions of households to participate or not in the PES program.However,neighborhood impacts on household participation in PES have rarely been addressed.This study explores potential neighborhood effects on villagers'enrollment in the Grain-to-Green Program(GTGP),one of the largest PES programs in the world,using data from China's Fanjingshan National Nature Reserve.We utilize a fixed effects logistic regression model in combination with the eigenvector spatial filtering(ESF)method to explore whether neighborhood size affects household enrollment in GTGP.By comparing the results with and without ESF,we find that the ESF method can help account for spatial autocorrelation properly and reveal neighborhood impacts that are otherwise hidden,including the effects of area of forest enrolled in a concurrent PES program,gender and household size.The method can thus uncover mechanisms previously undetected due to not taking into account neighborhood impacts and thus provides an additional way to account for neighborhood impacts in PES programs and other studies.
文摘目的分析急诊患者放弃有创抢救的原因并提出对策。方法选择2014年1月至2014年12月收入北京协和医院急诊抢救室的2673例患者，分为抢救组和放弃抢救组，对两组患者的基本情况、基础疾病、医疗费用支付方式、签署意见书的人员构成、患者的治疗情况以及预后进行分析。结果两组患者男女性别构成差异无统计学意义（x^2=1．86，P=0．173）；放弃抢救组患者年龄明显高于抢救组患者（69．5±12．5 vs．58．6±19．2岁，F=28．92，P=0．000）；放弃抢救组中北京以外的患者比例更高（51．90％ vs 44．01％，x^2=10．59，P=0．001）；放弃抢救组中患慢性心衰、慢性呼吸衰竭、慢性肝性脑病、慢性肾衰竭、恶性肿瘤等慢性疾病的比例更高（8．17％ vs ．3．03％，8．17％ vs ．2．61％，3．80％ vs ．1．16％，5．32％ vs．1．44％，11．98％ vs．2．28％，均P=0．000）；放弃抢救组中白费患者比例更高（52．09％vs．41．08％，x^2=20．87，P=0．000）；在签署意见书的人员构成方面，由患者本人签署的放弃抢救的比例明显高于同意抢救（3．04％ vs．0．42％，x^2=64．40，P=0．000），而患者的子女、配偶、父母、兄弟姐妹以及其他人员签署的同意抢救和放弃抢救的比例差异无统计学意义；Logistic回归分析结果显示患者高龄、非北京患者、患慢性基础病、自费、由患者本人签署意见书是放弃有创抢救的重要影响因素；放弃抢救组患者的病死率明显高于抢救组（19．39％ vs．7．68％，x^2=64．40，P=0．000）。结论放弃有创抢救治疗的患者多为高龄或属于慢性疾病终末期，急诊医务人员应继续关注这些患者，采用无创的手段进行治疗或减轻患者的痛苦。
