Doctoral Dissertation Research: Food Insecurity and Nonstandard Work among Low-income Rural Households, a Longitudinal Analysis.

PI和Co-PI：Diane McLaughlin和Alisha J.科尔曼博士论文研究：粮食不安全，非标准工作和低收入农村家庭0825235摘要本研究项目将进行一项小组研究，调查粮食不安全的预测因素，重点关注父母或家庭中主要和次要照顾者的就业特征。 粮食不安全是指一个家庭？它无法获得其成员所需的食物。 研究问题是：主要和次要照顾者的就业类型和特点（如工作小时数、就业天数/时间表、临时/长期工作、工作质量、身兼数职和收入可变性）与家庭粮食不安全有何关系？ 研究者将纳入到重要地点（如父母）的距离信息。工作、儿童保育和超市，以确定这些因素是否与粮食不安全有关，以及它们是否与就业特点相互作用，影响粮食不安全。 数据将来自家庭生活项目，该项目以宾夕法尼亚州和北卡罗来纳州有幼儿的农村低收入家庭为样本。 这些数据是纵向的，从研究的诞生开始就有一组家庭。的目标孩子，直到孩子三岁。 研究人员将使用面板数据和事件历史分析来模拟粮食不安全的转变。 将使用潜在类别分析来确定长期粮食不安全的模式。 这些技术将有助于了解工作特征的变化如何预测粮食安全状况的变化，同时控制竞争性解释。 这项研究将提高我们对粮食不安全预测因素的理解，并帮助记录非标准工作安排的影响。 政策影响将产生于确定现有方案，特别是联邦食品券方案，可以更好地满足由于就业特点而收入经常变化的家庭的需要。 通过纳入距离和位置数据，分析将有助于制定政策，以应对农村地区年轻家庭面临的与距离和孤立有关的挑战。 通过小组数据可以确定粮食不安全、工作安排和其他预测因素之间的关系。 迄今为止，大多数粮食不安全研究都确定了粮食不安全家庭的特征，拟议的研究很重要，因为它将确定与过渡到粮食不安全和摆脱粮食不安全有关的因素。 了解这些预测因素将有助于政策制定者和从业人员预防粮食不安全的发生，以及在粮食不安全发生后减轻粮食不安全。

PI and Co- PI: Diane McLaughlin and Alisha J. Coleman Doctoral Dissertation Research: Food Insecurity, Nonstandard Work, and Low-income Rural Households0825235 AbstractThis research project will undertake a panel study to investigate predictors of food insecurity focusing on characteristics of employment of parents or primary and secondary caregivers in the household. Food insecurity refers to a household?s inability to obtain the food necessary for its members. The research question is: How do type and characteristics of employment (e.g. number of hours worked, days/schedule of employment, temporary/permanent jobs, job quality, multiple job holding and variability in income) of the primary and secondary caregivers relate to household food insecurity? The investigator will incorporate information on distances traveled to important locations such as parents? work, childcare, and supermarkets to determine if these relate to food insecurity and if they interact with employment characteristics to influence food insecurity. Data will come from the Family Life Project, which features a purposive sample of rural low-income families with young children from Pennsylvania and North Carolina. The data are longitudinal, following a cohort of families from the birth of the study?s target child until that child is aged three. The investigator will use the panel data and event history analysis to model transitions into and out of food insecurity. Latent class analysis will be used to identify patterns in food insecurity over time. These techniques will contribute to understanding how changes in work characteristics predict changes in food security status, while controlling for competing explanations. The research will improve our understanding of the predictors of food insecurity and help document the effects of nonstandard work arrangements. Policy impacts will result from identifying ways that existing programs, especially the federal Food Stamp Program, can better meet the needs of households with frequent changes in income due to their employment characteristics. By incorporating distance and location data, the analysis will aid in developing policies directed to meeting challenges related to distance and isolation faced by young families living in rural areas. Panel data allow for a determination of relationships between food insecurity, work arrangements and other predictors. To date, most food insecurity research has identified characteristics of food insecure households, the proposed research is important because it will identify factors that relate to transitions into food insecurity and out of food insecurity. Understanding these predictors will assist policy makers and practitioners in preventing the onset of food insecurity, as well as alleviating food insecurity once it is experienced.