| Course | HEP 386 Assessing Strengths and Needs for Health Education and Promotion |
|---|---|
| Module | Module 3 |
| Paper type | Literature review matrix |
| Length | About 527 words, 4 pages |
| Format | APA 7 student paper |
| School | Arizona State University |
| Program | BS in Health Education and Health Promotion |
| Updated | October 2026 |
Free sample paper for HEP 386 Module 3
What the Evidence Says: Literature Review Data Collection on Food Insecurity Among Adults
Student Name
BS in Health Education and Health Promotion, Arizona State University
HEP 386: Assessing Strengths and Needs for Health Education and Promotion
Instructor Name
Month Day, Year
What the Evidence Says: Literature Review Data Collection on Food Insecurity Among Adults
Search Results
Searches in PubMed, CINAHL and Academic Search Ultimate, plus USDA and CDC sources, returned 412 records after duplicates were removed. After screening titles and abstracts against the criteria in my plan, I read 21 full texts and kept the eight most relevant and strongest for this matrix.
Matrix, Question 1: Food Insecurity and Adult Health
| Source | Design and sample | Key findings | Strengths and limits | Relevance to Yuma |
|---|---|---|---|---|
| (Seligman et al., 2010) | Cross-sectional; 5,094 low-income adults aged 18 to 65 in NHANES 1999 to 2004 | Food insecurity linked to self-reported hypertension (adjusted relative risk 1.20) and hyperlipidemia (1.30), and to measured hypertension (1.21) | Clinical measures; cross-sectional, so direction unclear | High chronic disease estimates in Yuma make this link important |
| (Gundersen & Ziliak, 2015) | Review of recent U.S. research | Food insecurity consistently linked to poorer health; SNAP substantially reduces food insecurity | Broad synthesis; not a systematic review | Frames the health case for the assessment |
| (Seligman et al., 2014) | California hospital admissions, 2000 to 2008 | Low-income residents' admissions for hypoglycemia were 27% higher in a month's final week than in its opening week | Large administrative data; ecological timing measure | Suggests monthly food budget cycles may matter for residents with diabetes |
| (Berkowitz et al., 2018) | Cohort; 16,663 adults from NHIS linked to MEPS | Food-insecure adults had about $1,863 more in annual health care spending after adjustment | Nationally representative; spending data not clinical outcomes | Useful for persuading funders and health systems |
Matrix, Question 2: Groups at Risk
| Source | Design and sample | Key findings | Strengths and limits | Relevance to Yuma |
|---|---|---|---|---|
| (Rabbitt et al., 2024) | Annual national survey of U.S. households | 13.5% of households food insecure in 2023 | Gold-standard measure; national only | National benchmark for county estimates |
| (Hill et al., 2011) | Survey of migrant farmworkers in Georgia | 62.8% lacked enough food; non-H-2A workers had nearly three times the risk; lack of cooking facilities and transportation added risk | Hard-to-reach group; one state, small study | Closest evidence for Yuma's agricultural workforce |
Matrix, Question 3: Programs That Work
| Source | Design and sample | Key findings | Strengths and limits | Relevance to Yuma |
|---|---|---|---|---|
| (Mabli & Ohls, 2015) | Quasi-experimental; about 6,500 SNAP households | SNAP participation reduced food insecurity by 6% to 17% and very low food security by 12% to 19% | Large sample; no randomized control | Supports outreach to eligible households |
| (Hager et al., 2023) | Pre-post evaluation of nine produce prescription programs; 2,064 adults and 1,817 children | Odds of food insecurity fell by about a third; blood pressure and HbA1c improved among adults with poor control | Multisite; no comparison group | A clinic-based model that could suit Yuma's produce economy |
Patterns
Across designs, food insecurity is tied to diet-sensitive chronic disease and higher health care costs. Risk concentrates among low-income and agricultural workers, and practical barriers such as transportation and cooking facilities matter. SNAP and produce prescriptions both show benefits, though neither was tested with randomization in these studies.
Gaps
I found no published study of food insecurity in Yuma County itself and little on Arizona farmworkers. Most studies are cross-sectional. The windshield survey and stakeholder interviews will need to supply local evidence on barriers and strengths.
References
Berkowitz, S. A., Basu, S., Meigs, J. B., & Seligman, H. K. (2018). Food insecurity and health care expenditures in the United States, 2011-2013. Health Services Research, 53(3), 1600-1620. https://doi.org/10.1111/1475-6773.12730
Gundersen, C., & Ziliak, J. P. (2015). Food insecurity and health outcomes. Health Affairs, 34(11), 1830-1839. https://doi.org/10.1377/hlthaff.2015.0645
Hager, K., Du, M., Li, Z., Mozaffarian, D., Chui, K., Shi, P., Ling, B., Cash, S. B., Folta, S. C., & Zhang, F. F. (2023). Impact of produce prescriptions on diet, food security, and cardiometabolic health outcomes: A multisite evaluation of 9 produce prescription programs in the United States. Circulation: Cardiovascular Quality and Outcomes, 16(9), e009520. https://doi.org/10.1161/CIRCOUTCOMES.122.009520
Hill, B. G., Moloney, A. G., Mize, T., Himelick, T., & Guest, J. L. (2011). Prevalence and predictors of food insecurity in migrant farmworkers in Georgia. American Journal of Public Health, 101(5), 831-833. https://doi.org/10.2105/AJPH.2010.199703
Mabli, J., & Ohls, J. (2015). Supplemental Nutrition Assistance Program participation is associated with an increase in household food security in a national evaluation. The Journal of Nutrition, 145(2), 344-351. https://doi.org/10.3945/jn.114.198697
Rabbitt, M. P., Reed-Jones, M., Hales, L. J., & Burke, M. P. (2024). Household food security in the United States in 2023 (Economic Research Report No. 337). U.S. Department of Agriculture, Economic Research Service. https://doi.org/10.32747/2024.8583175.ers
Seligman, H. K., Bolger, A. F., Guzman, D., López, A., & Bibbins-Domingo, K. (2014). Exhaustion of food budgets at month's end and hospital admissions for hypoglycemia. Health Affairs, 33(1), 116-123. https://doi.org/10.1377/hlthaff.2013.0096
Seligman, H. K., Laraia, B. A., & Kushel, M. B. (2010). Food insecurity is associated with chronic disease among low-income NHANES participants. The Journal of Nutrition, 140(2), 304-310. https://doi.org/10.3945/jn.109.112573
Reading the HEP 386 Module 3 assignment instructions
Literature Review Data Collection in HEP 386 Module 3 is worth 50 points. You carry out the search planned in Module 2, screen what you find, read the most relevant sources in full and record each one in an organized form, usually a matrix or annotated table, as the instructor's template directs. The goal is to gather and understand the evidence, not yet to write the review; the Module 4 first draft will be built from what you record now. The same module includes the windshield survey and a plan for stakeholder interviews. Record full citations as you go, since rebuilding them later wastes hours. Quality matters more than volume.
How the HEP 386 Module 3 example is put together
The sample opens with search numbers showing how many records were found, screened and read. The matrix is split into three tables, one for each review question, with columns for design and sample, key findings, strengths and limits and relevance to the community. Each row carries a parenthetical citation. Short sections on patterns and gaps close the assignment and point to the local evidence still needed. The search numbers at the top show how the student moved from hundreds of records to a short list, which demonstrates a systematic approach. The relevance column links each study back to the community, so the matrix already points toward the arguments the draft will make.
HEP 386 Module 3 rubric: what earns full marks
Data collection is worth 50 points. Readers look for enough relevant, credible sources, accurate summaries of each study's design and findings, honest notes on limitations and a clear link to the community being assessed. Marks drop when sources are mostly websites, when findings are copied from abstracts without understanding, when design is not recorded, when the matrix is not organized by question and when gaps are not identified. Strong submissions also show variety in design, combining national statistics, observational studies and program evaluations, and they recognize when a study's population differs from the community being assessed. Summaries that report a key number, not just a direction, are easier to use in the draft.
HEP 386 Module 3 help with common mistakes
Record the design and sample for every source; it decides how much weight the finding deserves. Write findings in your own words with the key number. Note one strength and one limit each time. Add a relevance column so you can see which sources matter most locally. Keep a count of what you searched and screened. If your matrix is growing faster than your understanding, the desk can help you prioritize. Read the methods and results of each study, not only the abstract. Group sources by question as you go. Flag any source you might drop if your matrix grows too long, and keep the strongest designs. Keep notes brief and consistent.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Arizona State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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HEP 386 Module 3 questions, answered
Where can I find a free HEP 386 Module 3 sample paper?
The full literature matrix on food insecurity and adult health is on this page.
What is a literature review matrix?
A table that records each source's design, sample, findings, strengths, limits and relevance.
How many points is HEP 386 literature review data collection worth?
50 points, among the largest assignments in the course.
Do produce prescription programs reduce food insecurity?
A multisite evaluation found the odds of food insecurity fell by about a third among participants.
What should I do when there is no local research?
Note the gap and plan to fill it with local data, observation and interviews.