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首页> 外文期刊>Journal of Economics and Sustainable Development >Identification and Intensity of Food Insecurity and Coping Strategies of Rural Households: The Case of Gombora and Misha District, Hadiya Zone, Southern Ethiopia
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Identification and Intensity of Food Insecurity and Coping Strategies of Rural Households: The Case of Gombora and Misha District, Hadiya Zone, Southern Ethiopia

机译:农村家庭粮食不安全和应对策略的识别与强度:埃塞俄比亚南部哈迪亚地区金博拉和米沙区的案例

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A clear identification and understanding intensity of food insecurity and coping strategies of rural households helps policy makers and planners formulate new policies that enhance food security. Therefore, this study was conducted to identify major causes of food insecurity and coping strategies of rural households. In order to achieve these objectives biophysical; demographic and socio-economic data were collected from 150 randomly selected households in Gombora and Misha district, hadiya zone, southern Ethiopia.In addition, secondary data were collected from relevant organizations and pertinent documents. Descriptive statistics such as mean, standard deviation and percentages were used for analyzing the data. Moreover, t-test and - test were employed to describe characteristics of food secure and food insecure groups. The survey result shows that about 72% of sample farmers were food insecure A logistic regression model was fitted to analyze the potential variables affecting household food insecurity in the study area. Among 14 explanatory variables included in the logistic model, 9 of them were significant at less than 10% probability level. These were family size, number of oxen owned, use of chemical fertilizer, size of cultivated land, farm credit use, total annual income per adult equivalent, food consumption expenditure, livestock owned, and off-farm income per adult equivalent. The estimated model correctly predicted 92% of the sample cases, 81% food secure and 96% food insecure.
机译:清晰的识别和理解农村粮食不安全和应对策略的强度有助于决策者和规划者制定加强粮食安全的新政策。因此,进行了本研究以确定农村粮食不安全和应对策略的主要原因。为了实现这些目标生物物理;从埃塞俄比亚南部的Gombora和Misha区的150个随机选择的家庭中收集了人口统计和社会经济数据。此外,从有关组织和相关文件收集二级数据。描述性统计数据如平均值,标准偏差和百分比用于分析数据。此外,使用T检验和试验来描述食品安全和食物不安全群的特征。调查结果表明,大约72%的样本农民是食品的不安全,拟合逻辑回归模型,以分析影响研究区内家庭食品不安全的潜在变量。在逻辑模型中包含的14个解释性变量中,其中9个在概率水平的概率水平不到10%以下是显着的。这些是家庭规模,牛交拥有数量,使用化肥,耕地大小,农业信用用途,每人等同,食品消费支出,牲畜拥有,以及每年成人的非农收入。估计模型预先预测了92%的样品案例,81%的食物安全和96%的食物不安全。

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