NU704 Unit 5 Causal Inference Paper Example

Does an Empty Pantry Cause a Low? A Unit 5 Causal Inference Paper on Food Budgets and Hypoglycemia Admissions

[Student Name]

Purdue University Global

NU704: Biostatistics, Epidemiology, and Social Determinants of Population Health

Unit 5 Causal Inference Paper

[Instructor Name]

[Date]

The writer's setting is composite; the studies cited and their findings are real.

The Association

Seligman et al. (2014) examined hospital admissions for hypoglycemia in California over several years, comparing low-income and higher-income populations by week of the month. Among the low-income population, admissions in a month's final week ran 27 percent above its opening week. There was no comparable pattern among higher-income patients. The authors linked the timing to exhaustion of food budgets, since benefits and paychecks often arrive at the start of the month.

The question for practice is whether running out of food causes hypoglycemia in patients on glucose-lowering medicines, or whether something else explains the pattern. If the link is causal, interventions that address food access, or that teach patients to adjust treatment when meals are missed, should reduce admissions.

Hill's Approach

In 1965, Hill set out viewpoints for deciding whether an observed association is likely to be causal. He was clear that none was a rule that must be met and that none, except time order, was strictly necessary; they were aids to judgment (Hill, 1965). Later writers have argued that the viewpoints remain useful when combined with modern methods and evidence from other disciplines (Fedak et al., 2015). Each is considered below for the food budget association.

Strength

A 27 percent relative increase is moderate, not large. Hill's own view was that a large effect is harder to dismiss as bias, while a modest one is not thereby excluded from being causal. This association is strong enough to matter at a population level, but not so strong that it could not be partly explained by other factors.

Consistency

Is the pattern seen elsewhere? Food insecurity has been associated with diabetes and other chronic conditions in national data on low-income adults (Seligman et al., 2010). That study, however, examined prevalence, not timing, and does not directly replicate the end-of-month pattern. Consistency is therefore partial.

Specificity

The rise appeared for hypoglycemia, a condition that missed meals plausibly produce, rather than across all admissions. Hill gave specificity limited weight, but it adds a little here.

Temporality

Temporality is the essential criterion: the cause must precede the effect. The design ties admissions to the point in the month when food is most likely to be scarce, which supports the right order. It does not show, for each patient, that food ran out before the low occurred.

The calendar provides the time order that individual records could not.

Biological Gradient

A dose-response pattern would show more admissions as food scarcity worsens. The study compared week to week, and the rise concentrated at the end of the month, which is consistent with a gradient over the month. Individual measures of how much food was missing were not available.

Plausibility and Coherence

The mechanism is well understood. Insulin and sulfonylureas lower glucose whether or not food is eaten, so a skipped meal on a usual dose can cause hypoglycemia. The association is coherent with what is known about diabetes treatment and about household food budgets.

Experiment

Experimental evidence would show that providing food, or adjusting medicines when food is short, reduces hypoglycemia. Such trials are few. This is the weakest part of the case and an opportunity for projects like the insulin discharge bundle to contribute practice-based evidence.

Analogy

Analogous patterns, such as end-of-month changes in other health outcomes in populations receiving monthly benefits, support the idea that monthly income cycles affect health, though they do not address hypoglycemia directly.

Alternative Explanations

Other explanations deserve consideration. Medication refills might cluster at the start of the month, changing doses. Alcohol use could vary by pay cycle. Hospital admitting patterns could differ by week. The higher-income comparison group helps, since such factors would likely affect both groups, but it cannot exclude explanations specific to low-income patients. The study was ecological and observational, so confounding at the individual level remains possible.

Judgment

Weighing the considerations, the association is plausibly causal: the time order fits, the mechanism is clear, the pattern is specific to hypoglycemia and absent in a comparison group, and the finding coheres with known biology. The evidence is not conclusive, because the strength is moderate, direct replication is limited and experimental evidence is lacking. In practice the bar is lower when the proposed actions cost little and carry almost no risk, and this evidence clears that bar.

How the Considerations Interact

The viewpoints are not independent votes. Temporality and plausibility together carry more weight than either alone, because a mechanism that operates in the right time order is the core of a causal story. Specificity and the null finding in higher-income patients reinforce each other: if a general seasonal or administrative cause were at work, both groups should show it. Weakness in experiment and limited replication pull the other way, and they matter most for the size of the effect rather than its existence. A reader who counts criteria met, six or seven of nine, misses this structure. The judgment depends on which considerations bear on the most likely alternative explanations, not on the tally.

Testing the Pattern Locally

The project can add a modest local test. If food budgets drive some glucose-related returns, those returns should cluster late in the month among patients whose admission screen flagged a food shortage, and not among the rest. Over a year the numbers will be small, so the analysis will be descriptive, a simple table of returns by week of the month and screen result, rather than a formal test. A clear pattern would strengthen the case for the food resource referral; its absence would not disprove the published finding but would suggest local causes matter more.

What It Means for the Project

The insulin discharge bundle will add three low-risk actions supported by this judgment: screening for food insecurity before discharge, teaching patients what to do with their insulin when a meal is missed, and connecting positive screens to food resources. The project will record the day of the month of each glucose-related return, which will allow a small local check of the pattern over time.

Conclusion

Hill's considerations do not deliver a verdict, but they organize the evidence. For the link between exhausted food budgets and hypoglycemia, they support a cautious causal judgment, enough to justify simple preventive steps, while showing where better evidence, especially from interventions, is still needed.

References

Fedak, K. M., Bernal, A., Capshaw, Z. A., & Gross, S. (2015). Applying the Bradford Hill criteria in the 21st century: How data integration has changed causal inference in molecular epidemiology. Emerging Themes in Epidemiology, 12, Article 14. https://doi.org/10.1186/s12982-015-0037-4

Hill, A. B. (1965). The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine, 58(5), 295-300. https://doi.org/10.1177/003591576505800503

Seligman, H. K., Bolger, A. F., Guzman, D., Lopez, 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