| Course | HLTH 5043 Evaluation of Determinants of Health |
|---|---|
| Module | Module 2 |
| Paper type | Determinants of health analysis |
| Length | 1,190 words, about 4 pages plus title and reference pages |
| Format | APA 7 student paper |
| School | American College of Education |
| Program | Master of Public Health |
| Updated | September 2026 |
Free sample paper for HLTH 5043 Module 2
Upstream of the Neonatal Unit: The Social, Structural and Behavioral Determinants Behind a County's Black-White Gap in Infant Deaths
Student Name
American College of Education
HLTH5043: Evaluation of Determinants of Health
Module 2 Assignment
Instructor Name
October 12, 2026
From Pattern to Causes
The first module documented a composite county's racial gap in infant deaths: 12.3 per 1,000 births for Black infants and 4.6 for White infants over three pooled years, with the widest gap in deaths related to preterm birth and low birth weight and a smaller but important gap in sudden unexpected infant deaths. It also showed that the gap persists among mothers with college degrees. This module asks why.
Answering that question requires a way to organize causes that operate at different distances from the outcome. A useful approach moves from upstream determinants, such as racism, residential segregation and economic policy, through midstream factors, such as stress, neighborhood conditions and access to care, to downstream factors close to the birth itself, such as infections, blood pressure and sleep environments. A multidisciplinary panel assembled by the March of Dimes weighed 33 proposed explanations for why Black women give birth early more often than White women and concluded that none of the causes close to birth, or in between, accounts for the gap on its own, that socioeconomic factors alone cannot explain its social patterning, and that chronic stress may act through neuroendocrine and immune pathways (Braveman et al., 2021). The analysis below follows that structure.
Upstream: Structural Racism and Segregation
Where people live is shaped by history and policy, including decades of discriminatory lending, zoning and highway construction. In the county, about 70% of Black residents live in eleven census tracts on the east side, where typical household incomes run near 50% of the countywide figure, grocery stores and pharmacies are scarce, and the only hospital with a neonatal intensive care unit is across the river. Segregation of this kind is not merely a backdrop. Pooling 42 studies, Mehra et al. (2017) found that among Black mothers, living in the most segregated neighborhoods compared with the least was associated with higher odds of preterm birth, an odds ratio of 1.17, and of low birth weight, an odds ratio of 1.13. Segregation concentrates poverty, environmental hazards and stress while limiting access to resources, which is why it sits at the top of the causal chain.
Midstream: Discrimination and Chronic Stress
That the gap survives among mothers with degrees points to a factor that education does not remove. Experiences of racial discrimination are one such factor. Collins et al. (2004), studying African American mothers in Chicago, found that lifetime exposure to interpersonal racial discrimination in three or more domains, such as at work, in housing or when receiving services, was associated with more than twice the odds of delivering a very low birth weight infant after adjustment, an adjusted odds ratio of 2.6, and that the association persisted across sociodemographic, biomedical and behavioral characteristics.
Chronic stress offers a plausible pathway. The March of Dimes review describes how sustained stress may affect preterm birth through neuroendocrine and immune mechanisms that lead to inflammation, through changes in the microbiome and response to infection, and through effects on chronic disease risk and behavior (Braveman et al., 2021). A mother's risk is shaped not only by the nine months of her pregnancy but by the years of stress that came before it.
Midstream: Health Care Access and Quality
Access to care matters, though less than is often assumed. In the county, Black mothers were more likely than White mothers to begin prenatal care after the first trimester, 31% compared with 17%, often because of transportation, Medicaid enrollment delays and inflexible work hours. Late care means later detection of high blood pressure, gestational diabetes and infections that raise the risk of preterm birth. Quality also varies: residents of the east side most often deliver at the community hospital without a neonatal intensive care unit, so the smallest and sickest babies must be transferred after birth. Yet access alone cannot explain the gap, since it persists among women with early prenatal care and private insurance. Health care is a place where disparities can be widened or narrowed, rather than their root cause.
Downstream: Behaviors and the Sleep Environment
Behavioral determinants explain part of the postneonatal gap, particularly sudden unexpected infant deaths. The American Academy of Pediatrics advises that babies sleep on their backs every time, alone on a firm, level mattress with nothing soft around them, in their parents' room but not their bed, and away from tobacco smoke (Moon et al., 2022). County surveys of new mothers show that Black mothers were less likely to report always placing their babies on their backs and more likely to report bed-sharing, often linked to crowded housing, lack of a crib and advice passed through families. Smoking during pregnancy, by contrast, was more common among White mothers in the county, which illustrates that behaviors do not uniformly favor one group and cannot by themselves explain the overall gap.
Behaviors are best understood as shaped by upstream conditions. A family without a crib, living in a crowded apartment, faces different choices from one with a nursery, which is why effective programs pair education with material support.
What the Community Says
Published studies and county data describe the pattern, but the mothers most affected can explain how the determinants feel from the inside. In listening sessions held by the health department with Black mothers on the east side, three themes recurred. Several described being dismissed when they reported symptoms during pregnancy, such as headaches or swelling, and waiting until symptoms became severe before anyone acted. Many described the daily strain of long commutes on unreliable buses to jobs without paid leave, which made keeping prenatal appointments a trade-off against income. And several said that advice about safe sleep felt disconnected from their circumstances, since they had no crib, shared a bedroom with other children, or were told different things by grandmothers, nurses and pediatricians. These accounts do not replace evidence, but they show how discrimination, economic strain and material hardship arrive together in one pregnancy, and they point to what a program would need to change.
Putting the Determinants Together
The determinants operate as a chain rather than a list. Segregation and structural racism concentrate poverty and stress in particular neighborhoods and expose Black women to discrimination throughout their lives. Chronic stress and its biological effects, together with later and lower-quality care, raise the risk of preterm birth, which accounts for the largest share of the gap. Crowded housing and limited resources shape sleep environments, contributing to sudden unexpected infant deaths. Interventions at any single point will help, but the evidence suggests that programs working only downstream, such as safe sleep education alone, will leave the larger share of the disparity untouched.
For program planning, the analysis points to three levels of action: policies that address housing and economic security; care models that reduce stress and improve continuity and trust during pregnancy; and practical supports such as cribs and home visits after birth. The next modules compare evaluation approaches and build a logic model for a program that works at the second and third levels while the county pursues the first.
References
Braveman, P., Dominguez, T. P., Burke, W., Dolan, S. M., Stevenson, D. K., Jackson, F. M., Collins, J. W., Driscoll, D. A., Haley, T., Acker, J., Shaw, G. M., McCabe, E. R. B., Hay, W. W., Thornburg, K., Acevedo-Garcia, D., Cordero, J. F., Wise, P. H., Legaz, G., Rashied-Henry, K., ... Waddell, L. (2021). Explaining the Black-White disparity in preterm birth: A consensus statement from a multi-disciplinary scientific work group convened by the March of Dimes. Frontiers in Reproductive Health, 3, Article 684207. https://doi.org/10.3389/frph.2021.684207
Collins, J. W., David, R. J., Handler, A., Wall, S., & Andes, S. (2004). Very low birthweight in African American infants: The role of maternal exposure to interpersonal racial discrimination. American Journal of Public Health, 94(12), 2132-2138. https://doi.org/10.2105/AJPH.94.12.2132
Mehra, R., Boyd, L. M., & Ickovics, J. R. (2017). Racial residential segregation and adverse birth outcomes: A systematic review and meta-analysis. Social Science & Medicine, 191, 237-250. https://doi.org/10.1016/j.socscimed.2017.09.018
Moon, R. Y., Carlin, R. F., Hand, I., & Task Force on Sudden Infant Death Syndrome and the Committee on Fetus and Newborn. (2022). Sleep-related infant deaths: Updated 2022 recommendations for reducing infant deaths in the sleep environment. Pediatrics, 150(1), Article e2022057990. https://doi.org/10.1542/peds.2022-057990
Reading the HLTH 5043 Module 2 instructions
HLTH 5043 Module 2 typically asks you to explain a health disparity by its determinants. Prompts usually ask you to identify social, economic, environmental, health care and behavioral factors that contribute to the disparity you documented, support each with evidence, and show how they interact. Many sections encourage a framework, such as the social determinants of health domains or an upstream-to-downstream model. Graders expect evidence for each claimed determinant, preferably from peer-reviewed studies, and specific connections to your population rather than general statements. A paper that names the pathway, for example how segregation leads to stress and how stress leads to early delivery, reads as analysis rather than a list. Include structural factors, not only individual behaviors, and see in Canvas whether a conceptual diagram is expected.
Inside the HLTH 5043 Module 2 example
The worked analysis opens by restating the documented pattern and choosing an upstream-to-downstream structure backed by a consensus review. Structural determinants come first, with local detail and meta-analytic evidence linking segregation to birth outcomes. Discrimination and chronic stress follow, supported by an adjusted estimate and a plausible biological pathway. Health care access and quality are weighed with local data and a realistic view of their share. Behavioral determinants are tied to specific causes of death and a current guideline, including a local finding that cuts the other way. The final section joins the determinants into a chain and sets out three levels of action for the modules that follow.
Reading the HLTH 5043 Module 2 rubric
Determinants analysis rubrics generally weigh breadth across levels, quality of evidence, specificity to the population and integration. The breadth criterion rewards covering structural, social, health care and behavioral determinants rather than behavior alone. Evidence earns points when claims rest on peer-reviewed research with effect sizes reported. Specificity to the community, using local data where possible, separates strong papers from generic ones. Integration, showing how determinants interact and which matter most, often earns the highest marks, and a simple diagram of the causal chain can make that integration visible. Implications for intervention are commonly required. Clear organization and APA 7 citation finish the scoring.
Common HLTH 5043 Module 2 mistakes, and how to avoid them
Determinants papers lose marks most often by listing factors without evidence, or by reducing a disparity to individual behavior. Another frequent problem is citing national findings without connecting them to the community in question. Students also treat each determinant in isolation. Organize by level. Support each claim with a study and a number. Include at least one structural factor. Show how the determinants connect, and say which ones your community could act on soonest. For a disparity in diabetes outcomes, asthma or maternal deaths instead, share your Module 1 findings and the rubric, and a Module 2 determinants analysis can be written from them.
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 American College of Education 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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HLTH 5043 Module 2 questions, answered
What does HLTH5043 Module 2 usually ask for?
The second HLTH5043 module often asks you to analyze the social, structural and behavioral determinants behind a health disparity, using evidence to explain how they produce the pattern you documented. In most sections the disparity carries over from your Module 1.
Why does the Black-White infant mortality gap persist among college-educated mothers?
Research points to factors education does not remove, such as lifetime experiences of racial discrimination and chronic stress, which may affect preterm birth through biological pathways.
How does residential segregation affect birth outcomes?
A meta-analysis found that Black mothers living in the most segregated neighborhoods had higher odds of preterm birth and low birth weight than those in the least segregated areas.
Where can I find a free HLTH 5043 Module 2 sample paper?
This page carries the complete Module 2 analysis of the determinants behind a county's racial gap in infant deaths, from segregation and discrimination to care access and safe sleep, organized upstream to downstream.
Are behaviors the main cause of health disparities?
Usually not. Behaviors matter, but they are shaped by upstream conditions such as housing and income, and programs that address behavior alone tend to leave most of a disparity in place.