Thesis advisor: Henry Braun / This study evaluates the accuracy, precision, and stability of three different methods of cross-survey analysis in order to determine their suitability for estimating the proportions of low-incidence populations. Population parameters of size and demographic distribution are necessary for planning and policy development. The estimation of these parameters for low-incidence populations poses a number of methodological challenges. Cross-survey analysis methodologies offer an alternative to generate useful, low-incidence population estimates not readily available in today's census without conducting targeted, costly surveys to estimate group size directly. The cross-survey methods evaluated in the study are meta-analysis of complex surveys (MACS), pooled design-based cross-survey (PDCS), and Bayesian multilevel regression with post-stratification (BMRP). The accuracy and precision of these methods were assessed by comparing the estimates of the proportion of the adult Jewish population in Canada generated by each method with benchmark estimates. The stability of the estimates, in turn, was determined by cross-validating estimates obtained with data from two random stratified subsamples drawn from a large pool of US surveys. The findings of the study indicate that, under the right conditions, cross-survey methods have the potential to produce very accurate and precise estimates of low-incidence populations. The study did find that the level of accuracy and precision of these estimates varied depending on the cross-survey method used and on the conditions under which the estimates were produced. The estimates obtained with PDCS and BMRP methodologies were more accurate than the ones generated by the MACS approach. The BMRP approach generated the most accurate estimates. The pooled design-based cross-survey method generated relatively accurate estimates across all the scenarios included in the study. The precision of the estimates was found to be related to the number of surveys considered in the analyses. Overall, the findings clearly show that cross-survey analysis methods provide a useful alternative for estimation of low-incidence populations. More research is needed to fully understand the factors that affect the accuracy and precision of estimates generated by these cross-survey methods. / Thesis (PhD) — Boston College, 2016. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

<p>  </p> <p>Food insecurity describes the lack of access to foods and affects 10.2% of general U.S. households and 27% of low-income households in 2021. Food insecurity is a pervasive public health concern in the United States and has been linked to poor dietary intake and diet quality, overweight and obesity (especially among women), and risk of other chronic diseases, such as diabetes, hypertension and dyslipidemia. </p> <p>To better understand food security status and address its associated health and dietary outcomes among low-income populations, a conceptualized model was built and served as research framework for the dissertation, including 1) internal factors and motivations, such as traits related to self-efficacy and sufficiency that may influence diet and health; 2) external factors of temporary support, such as financial benefits from assistance programs that low-income populations are eligible for that may influence diet and health; and 3) external factors of potentially long-term support, such as nutrition education programs targeting low-income groups that may foster internalized knowledge that could sustain impact and improvement of diet and health in the long-term. Each chapter of this dissertation addresses a component of the model.</p> <p>Cross-sectional analysis of a sample of rural veterans using food pantries quantified psychological traits related to self-motivation and efficacy including grit and help seeking, at the individual and internal factors level of the conceptualized model, and their links to food security and resource use, and revealed an inverse association between grit score and risk of food insecurity. The findings provided evidence for future interventions targeting food insecurity improvement to include education and resources that address traits related to self-efficacy, such as grit, among low-income populations to improve health outcomes directly or through improving food security or use of resources. </p> <p>Using nationally representative data, the second study investigated relationships between food assistance through the Supplemental Nutrition Assistance Program (SNAP) participation, a type of societal level external support, and dietary outcomes among low-income older U.S. adults. There were no differences in dietary quality, usual nutrient intake or risk of inadequacy between SNAP participants and eligible nonparticipants. Furthermore, results revealed a high prevalence of not meeting the Estimated Average Requirement from dietary sources for several nutrients (vitamins A, C, D, E, calcium, and magnesium) but the prevalence was lower when nutrients from dietary supplements were included. The results highlight a need for continued effort to improve nutrient and dietary intake among low-income older adults.</p> <p>External factors of potentially long-term support (e.g. nutrition education and food assistance) were evaluated for relationships with body mass index. A longitudinal sample of low-income women interested in participating in nutrition education through SNAP-Education (SNAP-Ed) was examined to determine the relationship between nutrition education (SNAP-Ed) and food assistance program participation through (SNAP, WIC), separately and in combination, with long-term changes in body mass index. No differences in changes of weight status over time were observed by nutrition education, food assistance, or combination participation. The prevalence of obesity was high among this sample, calling for targeted obesity prevention interventions and further support of healthy lifestyle promotion among low-income populations. </p> <p>The findings shown in this dissertation further reveal a high health burden among low-income groups. The studies filled several research gaps described in the conceptualized model. The results may be used to inform future tailored interventions to address food insecurity, dietary and health outcomes at individual and societal levels, incorporating internal motivation and external support to mediate health and dietary risks among low-income population.</p>