-
摘要:
在气候变化背景下,干旱可能会变得更严重和频繁。干旱不仅会影响经济,加剧环境污染和恶化,对生态环境造成严重的负面影响,还可通过多种途径直接或间接地危害人群健康。本文系统地收集和梳理国内外干旱与人群死亡关联的研究,介绍了干旱与全死因死亡、慢性非传染病死亡、传染病死亡以及伤害死亡的关联。研究结果表明干旱与人群死亡风险有关,可导致心肺疾病、癌症、痢疾、伤害等多种疾病死亡风险增加;干旱越严重死亡风险相应增加;农村男性、老龄人口与儿童是干旱的脆弱人群。但目前关于干旱与人群死亡的研究尚不够深入,今后需要开展更多的研究。本文综述了目前干旱与人群死亡的研究现状和存在的问题,并指出今后的研究方向,可为今后相关研究提供借鉴。
Abstract:Drought is expected to be more severe and frequent due to climate change. Drought exerts not only extensive impacts on economy and environment, but also direct or indirect impacts on human health. This review systematically collected studies exploring the association between drought and human mortality, and summarized the associations between drought and all-cause mortality, chronic non-communicable disease mortality, communicable disease mortality, and injury mortality. The results revealed that drought was significantly associated with human mortality, leading to an elevated mortality risk of cardiovascular diseases, respiratory diseases, cancers, diarrhea, and injuries; serious drought increased much more mortality risk than mild drought; males in rural areas, the elderly, and children were vulnerable populations to drought. However, in-depth studies on the association of drought with human mortality are limited, which calls for related studies in the future. This review summarized the current research status and existing problems in drought and population death, and pointed out the future research direction, which can provide reference for future related research.
-
GBZ 2.1—2019《工作场所有害因素职业接触限值 第1部分:化学有害因素》于2020年4月1实施。GBZ 2.1—2019与GBZ 2.1—2007相比增加了一些规范性引用文件,调整了部分术语、定义等内容,其中与职业接触限值相关的术语和定义主要有行动水平(action level)、接触水平(exposure level)、职业接触限值比值(ratio of occupational exposure level to OELs)、混合接触比值(ratio of mixed exposure)、峰接触浓度(peak exposures)等。GBZ 2.1—2019分强制性部分和推荐性部分,强制性部分为标准正文表1~表3,其余部分均为推荐性。GBZ 2.1—2019正文表1“工作场所空气中化学有害因素职业接触限值”是基于标准工时制度下(即8 h·d−1,40 h·周−1工作制)制定的。然而现实生活中很多企业实行的是非标准工时制度,针对非标准工时制度下化学有害因素职业接触限值调整的相关问题,GBZ 2.1—2019增加了对超过标准工时制度时接触化学有害因素的评价以及折减因子计算等内容。折减因子(reduction factor)是指当工作时间超过标准工时制度时调整化学有害因素职业接触限值需乘以的数值,调整后的平均接触限值(adjusted average exposure value, AAEV)=标准限值×折减因子。GBZ 2.1—2019附录A第7.4部分提出了职业接触限值调整的应用要求:对长时间工作的化学有害因素职业接触限值进行调整时,原则上只对规定有时间加权平均容许浓度(permissible concentration-time weighted average, PC-TWA)的物质进行标化;对最高容许浓度(maximum allowable concentration, MAC)或短时间接触容许浓度(permissible concentration-short term exposure limit, PC-STEL)、具有刺激性和臭味的物质,以及单纯刺激性、安全或健康风险极低、生物半衰期少于4 h或技术上实施困难的物质原则上不进行调整。
职业接触限值调整的最终目的是保护劳动者健康,调整的初衷是考虑到长时间工作可能会导致有害物质的吸收增加,致机体的负荷也随之增加;同时,随着代谢时间的缩短,有害物质的排出减少,有可能导致体内有害物质的蓄积,从而引起不良健康效应[1],因此,为了确保劳动者的身体健康,有必要对劳动者接触的有害物质的职业接触限值进行相应调整,为劳动者提供与常规的职业接触限值等效的防护水平[1]。职业接触限值调整的理论基础以有害物质的理化性质及生物半减期为依据。目前,国际上针对非标准工时制度下化学有害因素职业接触限值的调整大致可分为3类:⑴药代动力学的模型,以Hickey和Reist[2]以及Roach[3]药代动力模型为代表;⑵未考虑药代动力学的通用模型,以Brief和Scala[4]模型为代表;⑶综合考虑了药代动力学和毒理学的通用模型,以美国职业安全健康管理局(Occupational Safety and Health Administration, OSHA)和魁北克模型[5–6]为代表。在进行职业接触限值调整时,化学有害因素的药代动力学(生物半减期)是非常重要的,但是这方面信息很难获取,不适合用药代动力学模型进行调整。因此,在缺乏药代动力学资料的情况下,应优先考虑Brief和Scala模型,GBZ 2.1—2019也要求在实际应用时可参考Brief和Scala模型。
1. 职业卫生实践中引入“折减因子”后常见问题
1.1 职业接触限值调整的应用条件不能涵盖所有类型的工时制度
GBZ 2.1—2019附录A第7.3部分提出了职业接触限值调整的应用条件(每天工作超过8 h,可应用日调整公式;每周工作超过5 d和超过40 h时,可应用周调整公式),实际应用时可参考Brief和Scala模型。目前国内企业实行的工时制度越来越多样化,一些职业卫生技术服务机构在进行职业接触限值调整时,实际工作时间的计算没有统一的标准,常见于轮班工作制度实际工作时间的计算。不同轮班工作制,劳动者每周工作天数是不完全相同的,比如三班两转工作制的劳动者,有些周工作4 d(48 h),有些周工作5 d(60 h),根据周调整公式选择48 h,还是60 h进行计算,结果完全不一样。因此,针对非标准工时制度下劳动者实际工作时间的计算,建议采用工作周期的周平均接触小时数进行计算。
针对以上问题,需要了解工作周期和工作周期平均接触小时数的概念。工作周期是指完成一个工作循环周期所需要的时间,通常以“日”和“周”为基础重复循环[7]。例如,常见的标准工时制度,是以“日历周”为一个工作周期;常见的非标准工时制度,如轮班工作制中的三班两转,就是一种3周/21 d的工作周期。
工作周期周平均接触小时数是指在一个工作循环周期中,每周的平均工作小时数[7]。例如,常见的标准工时制度,其工作周期平均接触小时数为40 h·周−1;三班两转工作制中,工作循环周期为3周,其工作周期周平均接触小时数为56 h。对于轮班工作制,工作周期周平均接触小时数可通过“周总工时数/班次数”计算更简单。比如:三班两转工作制,周平均接触小时数(h)=24×7/3=56;四班三转工作制,周平均接触小时数(h)=24×7/4=42。以一例介绍应用:一家铅锌矿金属冶炼厂冶炼炉车间作业工人实行的是三班两转工作制,作业工人在铅冶炼过程中接触到铅及其化合物、二氧化硫、高温等多种职业病危害因素。对该冶炼车间三班两转作业工人接触的铅及其化合物、二氧化硫的职业接触限值调整如何计算?首先,鉴于作业工人实行的是三班两转工作制,通过分析可得作业工人工作周期的周平均接触小时数(h)=24×7/3=56,代入周调整应用公式进行计算可得周调整的折减因子=0.62;代入日调整应用公式计算可得日调整的折减因子=0.5,通过比较可知日调整折减因子比周调整折减因子更小更为保守,所以选择使用日调整进行计算。通过查询GBZ 2.1—2019中工作场所空气中化学有害因素职业接触限值,得知铅烟的PC-TWA=0.03 mg·m−3,铅尘的PC-TWA=0.05 mg·m−3;结合职业卫生现场调查可知作业工人接触职业危害因素以铅烟为主,通过计算可得铅烟的AAEV=0.03×0.5=0.015 mg·m−3,低于铅烟原PC-TWA,说明其判定标准比调整前更为严苛。GBZ 2.1—2019附录A第7.4部分规定对具有刺激性的物质原则上不需要调整,通过查阅资料,二氧化硫属于刺激性气体,不需要进行职业接触限值调整。值得注意的是,因作业工人实行的三班两转工作制(每班12 h),在进行职业病危害因素检测结果计算时,应以工作时间(12 h)作为权数进行加权平均浓度计算以代表整个工作日内作业工人的实际时间加权平均浓度(exposure concentration of time weighted average, CTWA),再以AAEV为标准进行结果判定。
1.2 与职业接触限值相关的部分术语的对应数值未明确是否随之调整
1.2.1 峰接触浓度
GBZ 2.1—2019增加了“峰接触浓度”的术语,峰接触浓度指短时间内(不超过15 min)空气中存在有害物质的最大浓度(峰值浓度)。存在峰值浓度,意味着劳动者极有可能在短时间内一次大量接触有害物质[8](其浓度可能是PC-TWA的数倍),存在急性健康效应的可能性。如果仅依靠长时间平均接触的监测数据,可能会掩盖峰的漂移值,为了控制这种健康效应,对于制定有PC-TWA无PC-STEL的化学有害物质,GBZ 2.1—2019建议使用峰接触浓度控制短时间的最大接触,目的是防止在一个工作日内在PC-TWA若干倍时的瞬时高水平接触导致快速发生急性不良健康效应[8]。GBZ 2.1—2019附录A第6.3部分对工作场所化学有害因素职业接触提出了控制要求:(1)制定有PC-TWA无PC-STEL的化学有害因素,要求当日实际测得的CTWA不得超过对应的PC-TWA值[8];(2)同时,劳动者接触水平瞬时超出PC-TWA值3倍的接触每次不得超过15 min,一个工作日期间不得超过4次,相继间隔不得短于60 min,而且在任何情况下都不能超过PC-TWA值的5倍[8]。当劳动者的实际工作时间超过标准工时制度时,PC-TWA需要进行调整,调整后平均接触限值用AAEV表示,那么实际峰接触浓度(concentration of peak exposure, CPE)的控制要求是以调整前PC-TWA作为参考依据,还是调整后AAEV作为参考依据,GBZ 2.1—2019并未进行详细说明,有待修订及完善。
关于峰接触浓度对应数值是否随PC-TWA调整问题,GBZ 2.1—2019并未进行详细说明,目前也未查到相关支持文献。从GBZ 2.1—2019峰接触浓度名词术语中可知,对于制定有PC-TWA但尚未制定PC-STEL的化学有害因素,应使用峰接触浓度控制短时间的接触。峰接触浓度是指在遵守PC-TWA的前提下,容许在一个工作日内发生的任何一次短时间(15 min)超出PC-TWA水平的最大接触浓度,其实质上与短时间接触浓度(concentration-short term exposure limit, CSTEL)相同,其评价理应与CSTE相同。根据GBZ 2.1—2019有关对MAC或PC-STEL、具有刺激性和臭味的物质,以及单纯刺激性、安全或健康风险极低、生物半衰期少于4 h或技术上实施困难的物质原则上不进行调整的规定,建议峰接触浓度的控制要求以调整前的PC-TWA作为参考依据。
1.2.2 行动水平
行动水平又称管理水平,最初定义来自GBZ/T 224—2010《职业卫生名词术语》。GBZ/T 224—2010将行动水平定义为“工作场所职业性有害因素浓度达到该水平时,用人单位需要采取包括监测、健康监护、职业卫生培训、职业危害告知等控制措施,一般是职业接触限值的一半”。GBZ 2.1—2019重新对行动水平进行定义,将原术语中的工作场所职业性有害因素浓度改为劳动者实际接触化学有害因素的水平,两者之间有本质区别。前者主要针对工作场所,而工作场所职业性有害因素浓度与劳动者接触水平有关系但不等同;后者主要以劳动者实际接触化学有害因素水平为主,劳动者职业病危害因素接触水平评估要求尽可能以个体采样为主,以反映劳动者的真实接触水平[9]。我国的职业接触限值是以劳动者为中心制定的,制定职业卫生标准的最终目的是为了保护劳动者健康,因此以劳动者实际接触化学有害因素的水平为参考依据定义行动水平更为科学。化学有害因素的行动水平一般以该因素容许浓度的1/2表示,不同的职业病危害因素因容许浓度不同,其行动水平也不相同。对于制定有PC-TWA的化学有害因素,其行动水平以1/2 PC-TWA表示;当劳动者实行非标准工时制度时,化学有害因素的PC-TWA值需要进行调整,调整后的平均接触限值以AAEV表示,那么其行动水平是以1/2 AAEV表示,还是以职业接触限值调整前的1/2 PC-TWA表示,GBZ 2.1—2019并未进行详细说明,有待修订及完善。此外,行动水平还涉及职业健康监护工作,当劳动者接触职业病危害因素浓度超过行动水平后,用人单位需要采取职业健康监护措施;而当职业健康监护措施有了明确的参考指标后,还需要配套解决职业健康监护管理监护周期、监护管理等方面的要求;化学有害因素职业接触限值中引入“折减因子”进行调整不但直接影响该化学有害因素的行动水平,还间接影响了该化学有害因素的职业健康监护工作周期。因此,在GBZ 2.1—2019引入“折减因子”进行职业接触限值调整后,还应参考行动水平对GBZ 188—2014关于职业健康监护的相关内容进行修订[10]。
因行动水平结果直接影响用人单位是否开展职业病危害因素监测、职业卫生培训、职业病危害告知、职业健康监护等相关工作。因此,行动水平结果表示尤为重要,到底是以PC-TWA调整前浓度的一半(1/2 PC-TWA)表示,还是以PC-TWA调整后浓度的一半(1/2 AAEV)表示,两者差别甚大。关于行动水平对应数值是否随PC-TWA调整问题,GBZ 2.1—2019并未进行详细说明,目前也未查到相关支持文献。考虑到行动水平、混合接触比值等术语对应数值与PC-TWA值存在变量关系,且没有特定的应用前提条件,因此,建议行动水平、混合接触比值以调整后PC-TWA作为参考依据。职业卫生技术服务机构在进行用人单位职业卫生评价时可以根据职业病危害因素检测结果对行动水平的高低给予不同结论,具体如下。
(1)劳动者实际接触化学有害因素水平低于行动水平情况。根据行动水平的定义,理论上该岗位/工种后续将不需要开展职业健康监护、职业病危害监测及告知等工作。值得注意的是,行动水平只是作为工作场所化学有害因素启动控制措施的一个“起点”,可作为参考依据。用人单位的日常职业卫生管理工作应严格遵守《中华人民共和国职业病防治法》《工作场所职业卫生管理规定》等法律法规的相关要求。
(2)劳动者实际接触化学有害因素水平高于行动水平情况。根据行动水平的定义,用人单位需要开展职业健康监护、职业病危害监测及告知、职业卫生培训等相关工作。尤其是用人单位的职业健康监护工作,GBZ 188—2014《职业健康监护技术规范》要求根据不同职业病危害因素种类、健康危害特性、劳动者接触水平、用人单位的防护措施、目标疾病的潜伏期等因素制定相应的职业健康检查周期。当有了行动水平这个参考指标后,GBZ 188—2014关于不同职业病危害因素的职业健康监护检查周期以及其他相关内容均可参考行动水平参数进行修订和完善。
2. 结语
GBZ 2.1—2019相比较GBZ 2.1—2007有许多创新,比如“折减因子”在职业卫生实践中的应用,就考虑到劳动者长时间工作可能会使有害物质吸收增加、代谢排出减少,从而引起不良健康效应,为了确保劳动者的身体健康从而引入“折减因子”对其职业接触限值进行相应调整,为劳动者提供与常规职业接触限值等效的防护水平,对于我国职业卫生工作来说是一种新思路、新变化。自GBZ 2.1—2019实施以来,职业卫生技术服务机构在开展职业卫生实践工作中引入了“折减因子”对相应化学有害因素进行职业接触限值调整,调整过程时常出现分歧。本文主要将职业卫生实践中关于引入“折减因子”进行职业接触限值调整及接触水平判定过程常见问题进行分析,提出配套的解决对策并举例说明,以便职业卫生技术服务人员能够更科学、更合理地开展职业卫生实践工作;同时认为需要尽快配套出台相应的指导规范文件,以促进用人单位职业病防治工作。
-
表 1 常见气象干旱指标
Table 1 Common meteorological drought indicators
指标 缩写 定义 考虑因子 特点 缺点 应用 降水量距平百分比 PA 反映某一时段降水量与同期
平均状态偏离程度的指标降水 计算简单、资料易于获取、
应用广泛,能直观反映降水
异常引起的干旱对干旱响应慢,不能反映
干旱的内在机理适用于半湿润、半干旱地区平均气温高于10 ℃的时间段干旱事件的监测与评估 相对湿润度 MI 反映某时段降水量与蒸散量
之间平衡状况的指标降水、蒸散 反映作物生长季节大气中的
水分平衡特征未考虑其他气象变量(如
温度、风速、辐射等)对水
分平衡的影响适用于作物生长季节月以上尺度的干旱监测与评估 标准化降水指数 SPI 表征某时段降水量出现概率
多少的指标降水 计算稳定,对干旱反应灵敏,
具有多时间尺度应用的特性仅基于降水,对于潜在蒸
散、气温与地表状态等的
表征存在欠缺适用于不同地区不同时间尺度干旱的监测与评估 标准化降水蒸散
指数SPEI 表征某时段降水量与蒸散量
之差概率多少的指标降水、蒸散 考虑到温度对干旱的影响,
结合SPI与PDSI的优点,不仅
能监测干旱是否发生,并且
可以反映多个时间尺度的
持续时间要素不考虑土壤特征和土地利用
变化对干旱的影响。在某些
情况下,这可能不能充分反
映干旱的真实情况适用于半湿润、半干旱地区不同时间尺度干旱的监测与评估 帕默尔干旱指数 PDSI 表征某时段某土地土壤实际
水分供应相当于当地气候适
宜水分供应亏缺程度的指标降水、蒸散、
径流、土壤
湿度能够考虑到降水、蒸散和径
流的平衡并且能够结合当地
土壤和植被特性资料处理与计算复杂,对
土壤湿度参数使用具有不
确定性,对干旱反应迟钝适用于月以上尺度的干旱监测与评估 气象干旱综合指数 MCI 考虑60 d有效降水、30 d内
蒸散以及季度尺度降水和
近半年尺度降水综合影响
的指标降水、蒸散 尽可能考虑到不同时间尺度
的干旱累积效应和不同时间
尺度的降水对干旱缓和或缓
解的作用考虑蒸散、降水权重不
同,对“骤发性”干旱的监
测反应迟缓适用于作物生长季节逐日气象干旱的监测和评估 -
[1] TRENBERTH K E, DAI A, VAN DER SCHRIER G, et al. Global warming and changes in drought[J]. Nat Climate Change, 2014, 4(1): 17-22. doi: 10.1038/nclimate2067
[2] 陈亚宁, 李玉朋, 李稚, 等. 全球气候变化对干旱区影响分析[J]. 地球科学进展, 2022, 37(2): 111-119. doi: 10.11867/j.issn.1001-8166.2022.006 CHEN Y N, LI Y P, LI Z, et al. Analysis of the impact of global Climate change on Dryland areas[J]. Adv Earth Sci, 2022, 37(2): 111-119. doi: 10.11867/j.issn.1001-8166.2022.006
[3] IPCC. Summary for policymakers [EB/OL]. [2023-01-01]. https://www.ipcc.ch/site/assets/uploads/sites/4/2022/11/SRCCL_SPM.pdf.
[4] IPCC. Climate change 2022-mitigation of climate change. contribution of working group iii to the sixth assessment report of the intergovernmental panel on climate change[M]. Cambridge: Cambridge University Press, 2022.
[5] UNCCD. Drought in Numbers 2022[EB/OL]. [2023-01-01]. https://www.unccd.int/resources/publications/drought-numbers.
[6] 王莺, 张强, 王劲松, 等. 21世纪以来干旱研究的若干新进展与展望[J]. 干旱气象, 2022, 40(4): 549-566. doi: 10.11755/j.issn.1006-7639(2022)-04-0549 WANG Y, ZHANG Q, WANG J S, et al. New progress and prospect of drought research since the 21st century[J]. J Arid Meteorol, 2022, 40(4): 549-566. doi: 10.11755/j.issn.1006-7639(2022)-04-0549
[7] 吴志勇, 白博宇, 何海, 等. 珠江流域1981—2020年水文干旱时空特征分析[J]. 河海大学学报(自然科学版), 2023, 51(1): 1-9. WU Z Y, BAI B Y, HE H, et al. Temporal and spatial characteristics of hydrological drought in the Pearl River Basin from 1981 to 2020[J]. J Hohai Univ (Nat Sci), 2023, 51(1): 1-9.
[8] 中国气象局国家气候中心. 中国气候公报(2022)[M]. 北京: 气象出版社, 2022. China Meteorological Administration. China climate bulletin (2022)[M]. Beijing: China Meteorological Press, 2022.
[9] SU B, HUANG J, FISCHER T, et al. Drought losses in China might double between the 1.5 °C and 2.0 °C warming[J]. Proc Natl Acad Sci USA, 2018, 115(42): 10600-10605. doi: 10.1073/pnas.1802129115
[10] 陶然, 张珂. 基于PDSI的1982—2015年我国气象干旱特征及时空变化分析[J]. 水资源保护, 2020, 36(5): 50-56. doi: 10.3880/j.issn.1004-6933.2020.05.008 TAO R, ZHANG K. PDSI-based analysis of characteristics and spatiotemporal changes of meteorological drought in China from 1982 to 2015[J]. Water Resources Prot, 2020, 36(5): 50-56. doi: 10.3880/j.issn.1004-6933.2020.05.008
[11] World Meteorological Organization. Atlas of mortality and economic losses from weather, climate and water extremes (1970-2019)[EB/OL]. [2023-01-01]. https://public.wmo.int/en/media/news/atlas-of-mortality-and-economic-losses-from-weather-climate-and-water-extremes-1970-2019.
[12] World Meteorological Organization. Atlas of mortality and economic losses from weather, climate and water extremes (1970-2012)[R]. Genève: World Meteorological Organization, 2014.
[13] 董安祥, 柳媛普, 李晓苹, 等. 黄河流域1922~1932年特大旱灾的特点及其影响[J]. 干旱气象, 2010, 28(3): 270-278. doi: 10.3969/j.issn.1006-7639.2010.03.005 DONG A X, LIU Y P, LI X P, et al. Characteristics and influence of the extreme drought event lasting Eleven years (1922-1932) in the Yellow River valley[J]. J Arid Meteorol, 2010, 28(3): 270-278. doi: 10.3969/j.issn.1006-7639.2010.03.005
[14] SHAW S, KHAN J, PASWAN B. Spatial modeling of child malnutrition attributable to drought in India[J]. Int J Public Health, 2020, 65(3): 281-290. doi: 10.1007/s00038-020-01353-y
[15] 国家统计局人口统计司. 中国人口统计年鉴-1989[M]. 北京: 科学技术文献出版社, 1989. Population Statistics Department of National Bureau of Statistics of China. China population statistics yearbook-1989[M]. Beijing: Science and Technology Literature Press, 1989.
[16] ABANYIE S K, SUNKARI E D, APEA O B, et al. Assessment of the quality of water resources in the Upper East Region, Ghana: a review[J]. Sustain Water Resour Manag, 2020, 6(4): 52. doi: 10.1007/s40899-020-00409-4
[17] NEIRA M, ERGULER K, AHMADY-BIRGANI H, et al. Climate change and human health in the Eastern Mediterranean and Middle East: Literature review, research priorities and policy suggestions[J]. Environ Res, 2023, 216: 114537. doi: 10.1016/j.envres.2022.114537
[18] ŠMEJKALOVÁ A H, BRZEZINA J. The effect of drought on PM concentrations in the czech Republic[J]. Aerosol Air Qual Res, 2022, 22(10): 220130. doi: 10.4209/aaqr.220130
[19] ASMALL T, ABRAMS A, RÖÖSLI M, et al. The adverse health effects associated with drought in Africa[J]. Sci Total Environ, 2021, 793: 148500. doi: 10.1016/j.scitotenv.2021.148500
[20] YUSA A, BERRY P, CHENG J J, et al. Climate change, drought and human health in Canada[J]. Int J Environ Res Public Health, 2015, 12(7): 8359-8412. doi: 10.3390/ijerph120708359
[21] WANG P, ASARE E, PITZER V E, et al. Associations between long-term drought and diarrhea among children under five in low- and middle-income countries[J]. Nat Commun, 2022, 13(1): 3661. doi: 10.1038/s41467-022-31291-7
[22] ORIEVULU K S, AYEB-KARLSSON S, NGEMA S, et al. Exploring linkages between drought and HIV treatment adherence in Africa: a systematic review[J]. Lancet Planet Health, 2022, 6(4): e359-e370. doi: 10.1016/S2542-5196(22)00016-X
[23] YAP M, TUSON M, TURLACH B, et al. Modelling the relationship between rainfall and mental health using different spatial and temporal units[J]. Int J Environ Res Public Health, 2021, 18(3): 1312. doi: 10.3390/ijerph18031312
[24] WEILNHAMMER V, SCHMID J, MITTERMEIER I, et al. Extreme weather events in europe and their health consequences - A systematic review[J]. Int J Hyg Environ Health, 2021, 233: 113688. doi: 10.1016/j.ijheh.2021.113688
[25] WANG B, WANG S, LI L, et al. The association between drought and outpatient visits for respiratory diseases in four northwest cities of China[J]. Climat Change, 2021, 167(1/2): 2.
[26] SALVADOR C, NIETO R, LINARE C, et al. Effects of droughts on health: Diagnosis, repercussion, and adaptation in vulnerable regions under climate change. Challenges for future research[J]. Sci Total Environ, 2020, 703: 134912. doi: 10.1016/j.scitotenv.2019.134912
[27] MISHRA A K, SINGH V P. A review of drought concepts[J]. J Hydrol, 2010, 391(1/2): 202-216.
[28] MIRYAGHOUBZADEH M, KHOSRAVI S A, ZABIHI M. A review of drought indices and their performance[J]. J Water Sustainable Dev, 2019, 6(1): 103-112.
[29] 气象干旱等级: GB/T 20481—2017[S]. 北京: 中国标准出版社, 2017. Grades of meteorological drought: GB/T 20481—2017[S]. Beijing: Standards Press of China, 2017.
[30] GASPARRINI A. Distributed lag linear and non-linear models in R: the package dlnm[J]. J Stat Softw, 2011, 43(8): 1-20.
[31] SALVADOR C, NIETO R, LINARES C, et al. Effects on daily mortality of droughts in Galicia (NW Spain) from 1983 to 2013[J]. Sci Total Environ, 2019, 662: 121-133. doi: 10.1016/j.scitotenv.2019.01.217
[32] SALVADOR C, NIETO R, LINARES C, et al. Quantification of the effects of droughts on daily mortality in Spain at different timescales at regional and national levels: a meta-analysis[J]. Int J Environ Res Public Health, 2020, 17(17): 6114. doi: 10.3390/ijerph17176114
[33] SALVADOR C, VICEDO‐CABRERA A M, LIBONATI R, et al. Effects of drought on mortality in macro urban areas of Brazil Between 2000 and 2019[J]. Geohealth, 2022, 6(3): e2021GH000534. doi: 10.1029/2021GH000534
[34] ALAM I, OTANI S, NAGATA A, et al. Short- and long-term effects of drought on selected causes of mortality in Northern Bangladesh[J]. Int J Environ Res Public Health, 2022, 19(6): 3425. doi: 10.3390/ijerph19063425
[35] LYNCH K M, LYLES R H, WALLER L A, et al. Drought severity and all-cause mortality rates among adults in the United States: 1968-2014[J]. Environ Health, 2020, 19(1): 52. doi: 10.1186/s12940-020-00597-8
[36] BERMAN J D, EBISU K, PENG R D, et al. Drought and the risk of hospital admissions and mortality in older adults in western USA from 2000 to 2013: a retrospective study[J]. Lancet Planet Health, 2017, 1(1): e17-e25. doi: 10.1016/S2542-5196(17)30002-5
[37] MCMICHAEL A J, WILKINSON P, KOVATS R S, et al. International study of temperature, heat and urban mortality: the 'ISOTHURM' project[J]. Int J Epidemiol, 2008, 37(5): 1121-1131. doi: 10.1093/ije/dyn086
[38] STANKE C, KERAC M, PRUDHOMME C, et al. Health effects of drought: a systematic review of the evidence[J]. PLoS Curr, 2013, 5: currents. dis. 7a2cee9e980f91ad7697b570bcc4b004.
[39] ABADI A M, GWON Y, GRIBBLE M O, et al. Drought and all-cause mortality in Nebraska from 1980 to 2014: Time-series analyses by age, sex, race, urbanicity and drought severity[J]. Sci Total Environ, 2022, 840: 156660. doi: 10.1016/j.scitotenv.2022.156660
[40] United Nations Climate Change. Introduction to gender and climate change[EB/OL]. [2023-01-01]. https://unfccc.int/gender.
[41] JERNECK A. What about gender in Climate Change? Twelve feminist lessons from development[J]. Sustainability, 2018, 10(3): 627. doi: 10.3390/su10030627
[42] SALVADOR C, NIETO R, LINARES C, et al. Drought effects on specific-cause mortality in Lisbon from 1983 to 2016: Risks assessment by gender and age groups[J]. Sci Total Environ, 2021, 751: 142332. doi: 10.1016/j.scitotenv.2020.142332
[43] LINDTJØRN B, ALEMU T, BJORVATN B. Population growth, fertility, mortality and migration in drought prone areas in Ethiopia[J]. Trans R Soc Trop Med Hyg, 1993, 87(1): 24-28. doi: 10.1016/0035-9203(93)90407-H
[44] LIN Y, LIU F, XU P. Effects of drought on infant mortality in China[J]. Health Econ, 2021, 30(2): 248-269. doi: 10.1002/hec.4191
[45] KIBRET G D, DEMANT D, HAYEN A. Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia[J]. PLoS One, 2022, 17(7): e0270879. doi: 10.1371/journal.pone.0270879
[46] LEE W S, LI B G. Extreme weather and mortality: Evidence from two millennia of Chinese elites[J]. J Health Econ, 2021, 76: 102401. doi: 10.1016/j.jhealeco.2020.102401
[47] DE WAAL A, TAFFESSE A S, CARRUTH L. Child survival during the 2002-2003 drought in Ethiopia[J]. Glob Public Health, 2006, 1(2): 125-132. doi: 10.1080/17441690600661168
[48] EBI K L, BOWEN K. Extreme events as sources of health vulnerability: Drought as an example[J]. Weather Climate Extrem, 2016, 11: 95-102. doi: 10.1016/j.wace.2015.10.001
[49] ALAM I, OTANI S, MAJBAUDDIN A, et al. The effects of drought severity and its aftereffects on mortality in Bangladesh[J]. Yonago Acta Med, 2021, 64(3): 292-302. doi: 10.33160/yam.2021.08.007
[50] MBALA F K, LONGO-MBENZA B, FUELE S M, et al. Impact des saisons, des années El Nino/La Nina et des précipitations sur la morbi-mortalité des accidents vasculaires cérébraux à Kinshasa[J]. J Mal Vasc, 2016, 41(1): 4-11. doi: 10.1016/j.jmv.2015.12.002
[51] WU K S, HUO X, ZHU G H. Relationships between esophageal cancer and spatial environment factors by using geographic information system[J]. Sci Total Environ, 2008, 393(2/3): 219-125.
[52] WU K, LI K. Association between esophageal cancer and drought in China by using geographic information system[J]. Environ Int, 2007, 33(5): 603-608. doi: 10.1016/j.envint.2007.01.001
[53] PAULL S H, HORTON D E, ASHFAQ M, et al. Drought and immunity determine the intensity of West Nile virus epidemics and climate change impacts[J]. Proc Roy Soc B Biol Sci, 2017, 284(1848): 20162078.
[54] BAKSHI B, NAWROTZKI R J, DONATO J R, et al. Exploring the link between climate variability and mortality in Sub-Saharan Africa[J]. Int J Environ Sustainable Dev, 2019, 18(2): 206-237. doi: 10.1504/IJESD.2019.099518
[55] BERRY H L, HOGAN A, OWEN J, et al. Climate change and farmers' mental health: risks and responses[J]. Asia Pacif J Public Health, 2011, 23(S2): 119S-132S.
[56] CHARLSON F, ALI S, BENMARHNIA T, et al. Climate change and mental health: a scoping review[J]. Int J Environ Res Public Health, 2021, 18(9): 4486. doi: 10.3390/ijerph18094486
[57] HANIGAN I C, SCHIRMER J, NIYONSENGA T. Drought and distress in southeastern Australia[J]. Ecohealth, 2018, 15(3): 642-655. doi: 10.1007/s10393-018-1339-0
[58] VINS H, BELL J, SAHA S, et al. The mental health outcomes of drought: a systematic review and causal process diagram[J]. Int J Environ Res Public Health, 2015, 12(10): 13251-13275. doi: 10.3390/ijerph121013251
[59] NICHOLLS N, BUTLER C D, HANIGAN I. Inter-annual rainfall variations and suicide in New South Wales, Australia, 1964-2001[J]. Int J Biometeorol, 2006, 50(3): 139-143. doi: 10.1007/s00484-005-0002-y
[60] HANIGAN I C, BUTLER C D, KOKIC P N, et al. Suicide and drought in New South Wales, Australia, 1970-2007[J]. Proc Natl Acad Sci USA, 2012, 109(35): 13950-13955. doi: 10.1073/pnas.1112965109
[61] FRIEL S, BERRY H, DINH H, et al. The impact of drought on the association between food security and mental health in a nationally representative Australian sample[J]. BMC Public Health, 2014, 14(1): 1102. doi: 10.1186/1471-2458-14-1102
[62] RICHARDSON R A, HARPER S, WEICHENTHAL S, et al. Extremes in water availability and suicide: Evidence from a nationally representative sample of rural Indian adults[J]. Environ Res, 2020, 190: 109969. doi: 10.1016/j.envres.2020.109969
[63] EDWARDS B, GRAY M, HUNTER B. A sunburnt country: the economic and financial impact of drought on rural and regional families in Australia in an era of climate change[J]. Austr J Labour Econom, 2009, 12(1): 109-131.
[64] UNDRR. GAR special report on drought 2021[EB/OL]. [2023-01-01]. https://www.undrr.org/publication/gar-special-report-drought-2021.
[65] MENDES C F, DOS SANTOS SEVERIANO J, MOURA G C D, et al. The reduction in water volume favors filamentous cyanobacteria and heterocyst production in semiarid tropical reservoirs without the influence of the N: P ratio[J]. Sci Total Environ, 2022, 816: 151584. doi: 10.1016/j.scitotenv.2021.151584
[66] BARROS M U G, WILSON A E, LEITÃO J I R, et al. Environmental factors associated with toxic cyanobacterial blooms across 20 drinking water reservoirs in a semi-arid region of Brazil[J]. Harmful Algae, 2019, 86: 128-137. doi: 10.1016/j.hal.2019.05.006
[67] MWAURA F, KOYO A O, ZECH B. Cyanobacterial blooms and the presence of cyanotoxins in small high altitude tropical headwater reservoirs in Kenya[J]. J Water Health, 2004, 2(1): 49-57. doi: 10.2166/wh.2004.0005
[68] POURIA S, DE ANDRADE A, BARBOSA J, et al. Fatal microcystin intoxication in haemodialysis unit in Caruaru, Brazil[J]. Lancet, 1998, 352(9121): 21-26. doi: 10.1016/S0140-6736(97)12285-1
[69] MCDERMOTT-LEVY R, SCOLIO M, SHAKYA K M, et al. Factors that influence climate change-related mortality in the United States: an integrative review[J]. Int J Environ Res Public Health, 2021, 18(15): 8220. doi: 10.3390/ijerph18158220
[70] SCHLEUSSNER C F, DONGES J F, DONNER R V, et al. Armed-conflict risks enhanced by climate-related disasters in ethnically fractionalized countries[J]. Proc Natl Acad Sci USA, 2016, 113(33): 9216-9221. doi: 10.1073/pnas.1601611113
[71] SAPIR D G. Natural and man-made disasters: the vulnerability of women-headed households and children without families[J]. World Health Stat Q, 1993, 46(4): 227-233.
[72] KELLEY C P, MOHTADI S, CANE M A, et al. Climate change in the Fertile Crescent and implications of the recent Syrian drought[J]. Proc Natl Acad Sci USA, 2015, 112(11): 3241-3246. doi: 10.1073/pnas.1421533112
[73] KANIEWSKI D, VAN CAMPO E, WEISS H. Drought is a recurring challenge in the Middle East[J]. Proc Natl Acad Sci USA, 2012, 109(10): 3862-3867. doi: 10.1073/pnas.1116304109
[74] ELAGIN D. Opium poppy in Afghanistan: The determinants of cultivation[J]. Asia Africa Today, 2020, 11: 48-55.
[75] SMITH L T, ARAGÃO L E O C, SABEL C E, et al. Drought impacts on children's respiratory health in the Brazilian Amazon[J]. Sci Rep, 2014, 4: 3726. doi: 10.1038/srep03726
[76] PETERSON T C, KARL T R, KOSSIN J P, et al. Changes in weather and climate extremes: State of knowledge relevant to air and water quality in the United States[J]. J Air Waste Manag Assoc, 2014, 64(2): 184-197. doi: 10.1080/10962247.2013.851044
[77] SHAH A S, LANGRISH J P, NAIR H, et al. Global association of air pollution and heart failure: a systematic review and meta-analysis[J]. Lancet, 2013, 382(9897): 1039-1048. doi: 10.1016/S0140-6736(13)60898-3
[78] YANG B Y, QIAN Z M, HOWARD S W, et al. Global association between ambient air pollution and blood pressure: A systematic review and meta-analysis[J]. Environ Pollut, 2018, 235: 576-588. doi: 10.1016/j.envpol.2018.01.001
[79] DU Y, XU X, CHU M, et al. Air particulate matter and cardiovascular disease: the epidemiological, biomedical and clinical evidence[J]. J Thorac Dis, 2016, 8(1): E8-e19.
[80] PIAO S, CIAIS P, HUANG Y, et al. The impacts of climate change on water resources and agriculture in China[J]. Nature, 2010, 467(7311): 43-51. doi: 10.1038/nature09364
[81] BANDYOPADHYAY N, BHUIYAN C, SAHA A K. Heat waves, temperature extremes and their impacts on monsoon rainfall and meteorological drought in Gujarat, India[J]. Nat Hazards, 2016, 82(1): 367-388. doi: 10.1007/s11069-016-2205-4
[82] DEZETTER M, LE GALLIARD J F, LEROUX-COYAU M, et al. Two stressors are worse than one: combined heatwave and drought affect hydration state and glucocorticoid levels in a temperate ectotherm[J]. J Exp Biol, 2022, 225(7): jeb243777. doi: 10.1242/jeb.243777
[83] RAYMOND C, HORTON R M, ZSCHEISCHLER J, et al. Understanding and managing connected extreme events[J]. Nat Climate Change, 2020, 10(7): 611-621. doi: 10.1038/s41558-020-0790-4
[84] MANSOOR S, KHAN T, FAROOQ I, et al. Drought and global hunger: biotechnological interventions in sustainability and management[J]. Planta, 2022, 256(5): 97. doi: 10.1007/s00425-022-04006-x
[85] Scrimshaw N S. The phenomenon of famine[J]. Annu Rev Nutr, 1987, 7: 1-22. doi: 10.1146/annurev.nu.07.070187.000245
[86] KIDANE A. Mortality estimates of the 1984-85 Ethiopian famine[J]. Scand J Soc Med, 1990, 18(4): 281-286. doi: 10.1177/140349489001800409
[87] LIM S S, VOS T, FLAXMAN A D, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010[J]. Lancet, 2012, 380(9859): 2224-2260. doi: 10.1016/S0140-6736(12)61766-8
[88] DEY N, ALAM M, SAJJAN A, et al. Assessing environmental and health impact of drought in the Northwest Bangladesh[J]. J Environ Sci Nat Resour, 2012, 4(2): 89-97.
计量
- 文章访问数: 222
- HTML全文浏览量: 33
- PDF下载量: 58