StatisticsData analysisEpidemiological measures

BRFSS odds ratio discussion: 2x2 table calculation guide

A two-part hands-on exercise on real CDC surveillance data: replicate a specified cross tabulation — 2015 Arizona, binge drinking by depression — and compute the odds ratio, then design your own two-variable association; the graded subtlety is whether the odds ratio approximates relative risk here, and why.

Aug 11, 2026

Editorial process

Last reviewed · August 11, 2026

Written by

Aaron Bishop

MA, Education

assignment interpretation and research-methods coaching across disciplines

Reviewed by

Dr. Nathan Cole

PhD, Rhetoric & Composition

Argumentation and thesis development

On this page

Interpret the task
Assignment instructions
Deliverables
Proposed outline
Research plan
Reference shortlist
Final review

What is the odds ratio assignment actually probing?

Part 1 is fully specified — the brief walks you through the BRFSS Web-Enabled Analysis Tool click by click (2015, Arizona, binge drinking as the row, depressive-disorder diagnosis as the column, sample size as the statistic) — and that specificity is your safety rail: the 2×2 table you extract is checkable, so transcribe the four cells exactly and label them in the standard a/b/c/d layout before touching the formula. The odds ratio itself is the cross-product, (a×d)/(b×c), and the brief demands your work be visible: show the table, present the formula, walk the arithmetic. The interpretation sentence has a standard form worth using precisely — the odds of ever-diagnosed depression among binge drinkers are OR times the odds among non-binge-drinkers — and 'odds' versus 'risk' in that sentence is exactly the distinction the assignment is probing.

Because the follow-up question — is the odds ratio a good estimate of the relative risk in this situation? — is the conceptual heart of the assignment. The rule: the odds ratio approximates relative risk when the outcome is rare (the standard threshold cited is roughly under 10% prevalence), and diverges — always further from 1 — as the outcome gets common. Depression diagnoses in BRFSS data are not rare; roughly a fifth of adults report one, so the honest answer engages that: the OR here overstates the relative risk, and your 'why or why not' should state the rare-disease assumption and check it against the prevalence visible in your own table. There is a second, subtler point available for strong submissions: in a cross-sectional survey, both exposure and outcome are measured at once, so no temporal direction can be claimed — the association says nothing about which came first.

Part 2 hands you the same machinery with free choice of variables, and the choice is graded through 'discuss the public health importance of the association' — pick a pair where the association plausibly matters (a behaviour and a chronic condition, a screening behaviour and a demographic) and where cell sizes are large enough that the OR is stable. Same deliverables: the 2×2 table shown, the formula presented, the interpretation written in odds language, and the importance argued rather than asserted.

Likely learning objectives

Inferred from the brief — check these against your own rubric.

01
Extract a 2×2 contingency table from the BRFSS Web-Enabled Analysis Tool following the brief's exact specification.
02
Calculate an odds ratio via the cross-product formula with all work shown, and interpret it in correct odds language.
03
Evaluate the odds ratio as an estimate of relative risk using the rare-disease assumption, checked against the outcome's actual prevalence in the table.
04
Design a defensible second association — variables with public health stakes and adequate cell sizes — and argue its importance.

Assignment instructionsQuoted verbatim

Read the full question

Review every instruction before using the planning guidance that follows.

Data can be qualitative or quantitative. Qualitative data is helpful to generate a hypothesis and gather information if little is known about an expected association. Focus groups, key informant interviews, and case studies are types of qualitative data collection methods used to identify common themes from which to build a hypothesis. Quantitative data collection and analysis is used to test a hypothesis and make comparisons to determine the direction and strength of a potential association. The Behavioral Risk Factor Surveillance System (BRFSS) is cross-sectional panel survey used to collect quantitative data on adult behaviors and risk factors. It is one of the largest U.S. health data collection efforts. The data can be used to analyze associations on a state or country level. Follow the steps to obtain a 2×2 contingency table (also known as a “cross tabulation”) crossing binge drinking with depression. 1. Retrieve the “BRFSS Web-Enabled Analysis Tool” resource provided in the Topic Materials. 2. Select “Cross Tabulation.” 3. Select “2015” for the year. 4. Select “Arizona” for the state. 5. Select “Alcohol Consumption: Binge drinkers (males having five or more drinks on one occasion, females having four or more drinks on one occasion)” for Step 2 Select Row. 6. Select “Chronic Health Conditions: Ever diagnosed with a depressive disorder, including depression, major depression, dysthymia, or minor depression” for Step 3 Select Column. 7. Skip Steps 4 and 5. 8. Select “Sample Size” for Step 6 Select Statistics and run the report for the cross tabulation. Part 1 Using the data from the cross tabulation results, calculate the odds ratio for depression among those exposed to binge drinking. Interpret the odds ratio and discuss if the odds ratio is a good estimate of the relative risk in this situation. Why or why not? Show your 2×2 table and all calculations. Present or describe the formula you used to arrive at your answer. Calculating Odds Ratio Discussion Part 2 Use the Topic Material, “BRFSS Web-Enabled Analysis Tool,” located on the CDC website, and run a report for two variables of interest to you. Create a 2×2 table and calculate the odds ratio for this association. Interpret the odds ratio and discuss the public health importance of the association. Show your 2×2 table. Present or describe the formula you used to arrive at your answer. Refer to the “Creating a 2×2 Contingency Table” resource for guidance in creating 2×2 contingency tables. General Requirements APA style is not required, but solid academic writing is expected. This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance. Use the “BRFSS Web Enabled Analysis Tool,” located on the Centers for Disease Control and Prevention (CDC) website, to complete the topic assignment. URL: https://nccd.cdc.gov/weat/#/

Turn the brief into deliverables

01
Part 1: the 2×2 table from the specified cross tabulation (2015, Arizona, binge drinking × depressive disorder), the odds ratio calculation with formula presented, the interpretation, and the discussion of whether the OR estimates relative risk here — why or why not.
02
Part 2: a report on two variables of your choosing from the same tool, with the 2×2 table shown, the odds ratio calculated and interpreted, and the public health importance of the association discussed.
03
Solid academic writing (APA not required), rubric reviewed, submitted through LopesWrite, per the brief.

How should the two BRFSS parts be worked?

Extract the specified table

Follow the brief's eight steps in the BRFSS tool exactly — year, state, row, column, statistic — and transcribe the four cells into a labelled 2×2 table.

Compute and interpret the odds ratio

Apply the cross-product formula with visible arithmetic, then interpret in the standard odds sentence with the comparison group explicit.

The relative-risk verdict

State the rare-disease assumption, read the depression prevalence off your own table, and conclude whether the OR is a good estimate of relative risk in this situation — with the direction of its bias when the outcome is common.

Part 2: your association

Choose two BRFSS variables with a plausible health mechanism and workable cell sizes, rerun the tool, and produce the same package: table, formula, calculation, interpretation.

The public health importance

Argue why your Part 2 association matters — the populations affected, what surveillance of it enables, what intervention it might inform — as a discussion, not a declaration.

Which sources define the OR and its rare-disease limit?

Recommended databases

CDC BRFSS Web-Enabled Analysis Tool (the assignment's instrument)
PMC
Course Topic Materials

Search sequence

1.
Open the BRFSS WEAT tool and run Part 1's specified cross tabulation before reading anything else — the table anchors every later step.
2.
Read the odds-ratio explainer for the formula, the interpretation language, and the rare-disease assumption in citable form.
3.
Check the BRFSS overview so your writeup can describe the survey design (cross-sectional, self-report) accurately.
4.
Browse the tool's variable lists for Part 2 candidates before committing; run two or three candidate pairs and keep the one with stable cells and a story.

Reference shortlist

These are authoritative starting points, not a ready-made bibliography. A qualified reviewer must confirm that each source fits the assignment and supports the claim beside which it is cited.

Nothing here is cleared for citation until you have read it.

01
Explaining Odds Ratios
Journal of the Canadian Academy of Child and Adolescent Psychiatry (via PMC) · 2010
The standard citable explainer: the 2×2 layout, the cross-product formula, correct interpretation language, and the rare-disease condition under which the OR approximates relative risk.
02
Behavioral Risk Factor Surveillance System
Centers for Disease Control and Prevention · 2024
The survey behind the data — its cross-sectional, self-reported design is what your relative-risk and causation caveats rest on.
03
Behavioral Risk Factor Surveillance System: Web-Enabled Analysis Tool
Centers for Disease Control and Prevention · 2024
The assignment's own instrument, as the brief's URL points — where both parts' cross tabulations are run.

Review before submission

Common mistakes

Interpreting the odds ratio in risk language ('binge drinkers are X times more likely') — the OR is a ratio of odds, and the distinction is the assignment's point.
Answering the relative-risk question with the memorised rule but never checking depression's actual prevalence in your own table, which is what 'in this situation' asks for.
Mislabelling the 2×2 cells so the cross-product silently computes the wrong ratio — fix the a/b/c/d convention before calculating.
Hiding the arithmetic when the brief says three times to show the table and present the formula.
Choosing Part 2 variables with tiny cells or no plausible health connection, which makes the required importance discussion unwritable.
Claiming causation or direction from a cross-sectional survey — the design measures exposure and outcome simultaneously.

Submission checklist

Part 1 table matches the tool's output for the specified selections; cells labelled a/b/c/d.
Odds ratio formula presented and arithmetic shown for both parts.
Interpretations written in odds language with the comparison group named.
The relative-risk discussion cites the rare-disease assumption and the outcome prevalence from your table.
Part 2's variables named, justified, and their association's public health importance argued.
Rubric reviewed; submitted via LopesWrite.

Use this guide to plan and review your own work. Follow your institution's rules and read our academic-integrity policy.