five

Food Insecurity Experience Scale 2022 - Mauritius

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microdata.worldbank.org2023-09-26 更新2025-01-22 收录
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Abstract --------------------------- Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ . The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity. These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys. Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error. Geographic coverage --------------------------- National Analysis unit --------------------------- Individuals Universe --------------------------- Individuals of 15 years or older with access to landline and/or mobile phones. Kind of data --------------------------- Sample survey data [ssd] Sampling procedure --------------------------- NA Exclusions: NA Design effect: 1.56 Mode of data collection --------------------------- Computer-Assisted Telephone Interviewing [CATI] Cleaning operations --------------------------- Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model. Sampling error estimates --------------------------- The margin of error is estimated as 3.9. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

摘要 ---------------------------------------- 可持续发展目标(SDG)2.1项承诺各国结束饥饿,确保全年所有人都能获得安全、营养充足的食物。指标2.1.2,‘基于食物不安全经验量表(FIES)的食物不安全普遍率’,提供了国际上可比的估计,用以衡量面临食物获取困难的人口比例。更详细的背景信息可在http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ 查阅。 基于FIES的指标是通过FIES调查模块编制的,包含8个问题。可以计算两个指标: 1. 经历中度或严重食物不安全的人口比例(SDG指标2.1.2), 2. 经历严重食物不安全的人口比例。 这些数据由联合国粮食及农业组织(FAO)通过盖洛普全球民意调查收集。有关方法的详细信息,请参阅:https://www.gallup.com/178667/gallup-world-poll-work.aspx。国家机构也可以通过在国家代表性调查中包含FIES调查模块来收集FIES数据。 微观数据可用于计算国家级的指标2.1.2。计算此指标的具体说明可在文档标签页中的方法论文件中找到。不建议在次国家级别分解结果,因为估计将受到大量抽样和测量误差的影响。 地理覆盖范围 ---------------------------------------- 全国 分析单元 ---------------------------------------- 个人 总体 ---------------------------------------- 15岁及以上、拥有固定电话和/或移动电话的个人。 数据类型 ---------------------------------------- 样本调查数据[ssd] 抽样程序 ---------------------------------------- NA 排除项:NA 设计效应:1.56 数据收集方式 ---------------------------------------- 计算机辅助电话访谈[CATI] 数据清洗操作 ---------------------------------------- 统计验证评估了FIES数据的收集质量,通过测试其与Rasch模型假设的一致性。该分析涉及对多个统计量的解释,这些统计量揭示了1)在特定环境中表现不佳的项目,2)具有高度异常响应模式的案例,3)可能重复的项目对,以及4)由测量模型解释的总变异中占人口总变异的比例。 抽样误差估计 ---------------------------------------- 误差范围估计为3.9。这是在95%置信水平下围绕比例计算的。最大误差范围是在假设报告百分比为50%的情况下计算的,并考虑了设计效应。
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