Climate change impact on household food security and child undernutrition

气候变化对家庭粮食安全和儿童营养不良的影响

• 批准号: 427397520
• 负责人: Professor Dr. Rainer Sauerborn, Ph.D.
• 金额: --
• 依托单位: Heidelberger Institut für Global Health (HIGH)
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/427397520?language=en
• 关键词: Climate; change; impact; household; food

This project aims to quantify the contribution of disturbed rainfall patterns to the quantity of crop harvest, and its impact on household food security to provide nutritious foods consumed by children under 5 years of age. The assumed consequences are chronic undernutrition (stunting) and micronutrient deficiency in children under 5.In order to draw linkages between weather and nutrition, three steps are applied simultaneously: firstly, the validation of the exposure will be done by developing a rainfall index capturing the suitability of daily rainfall for the growth of major crop plants of the respective regions. Secondly, for determining the household crop harvest outcome, we will use the already locally validated quantification of harvest at the household plot level of households in our sample. Thirdly, we will assemble a dynamic cohort of 2000 children aged 0-5 years. These steps will be done in both study areas in the Nouna HDSS in Burkina Faso and in the Kisumu HDSS in Kenya over the 3 (+3) year lifetime of the Research Unit. Twice a year, a socioeconomic and nutritional questionnaire will be applied to the parents on their household food security situation and their child’s diet, and selected anthropometric measurements are taken from all children in the sample.The relationship between rainfall (exposure) and its consequences (direct outcome: impact on harvest quantity, indirect outcome: influence on household food security and childhood undernutrition) will be called by ERFs (exposure-response functions) derived from hierarchical Bayesian analyses, more specifically distributed-lag non-linear modelling. We will be able to compare the weather-related association with harvest, food security and child undernutrition with a large array of co-variables, e.g. socioeconomic household variables, previous diseases episodes in the children, and household expenditures and incomes through subsistence farming. In a final step, the ERFs will be incorporated into climate impact models, downscaled to the study area at a 12km by 12km resolution by our central project team (CP2). This will enable us to make projections of climate-nutrition impact for short- and long-term policy relevant time horizons (2030, 2050, 2100).

该项目的目的是量化受干扰的降雨模式对作物收成数量的贡献及其对家庭粮食安全的影响，以提供5岁以下儿童所消费的营养食品。假设的后果是5岁以下儿童长期营养不良（发育迟缓）和微量营养素缺乏症。为了确定天气与营养之间的联系，同时采取了三个步骤：首先，将通过制定一个降雨指数来验证暴露情况，该指数反映了每日降雨量对各地区主要作物生长的适宜性。其次，为了确定家庭作物收获结果，我们将使用已经在当地验证的量化收获在我们的样本家庭的家庭地块水平。第三，我们将汇集一个由2 000名0-5岁儿童组成的动态队列。这些步骤将在研究股3年（+3年）的存在期内，在布基纳法索努纳人类发展和社会调查和肯尼亚基苏穆人类发展和社会调查的两个研究领域内完成。每年两次向父母发出社会经济和营养问题单，询问他们的家庭粮食安全情况和他们子女的饮食，并对抽样中的所有儿童进行有选择的人体测量。（暴露）及其后果（直接结果：对收获量的影响，间接结果：对家庭粮食安全和儿童营养不良的影响）将由从分层贝叶斯分析、更具体地说是分布滞后非线性建模中得出的ERF（确定-响应函数）来调用。我们将能够将天气与收成、粮食安全和儿童营养不良的相关性与大量协变量进行比较，例如社会经济家庭变量、儿童以前的疾病发作以及通过自给农业的家庭支出和收入。在最后一步中，ERF将被纳入气候影响模型，由我们的中央项目团队（CP 2）以12公里× 12公里的分辨率缩小到研究区域。这将使我们能够预测短期和长期政策相关时间范围（2030年，2050年，2100年）的气候营养影响。