Cross-sectional and Ecological Studies – Quick Reference

Cross-sectional studies

• What is a cross-sectional study?
  • Measures exposures and/or outcomes at one point in time.
  • Time concept: a point in time (a specific date, event, or period).
• What do cross-sectional studies measure?
  • Prevalence: the proportion of a defined population who have a disease at a point in time.
  • Prevalence formula: \text{Prevalence} = \frac{\text{Number with disease at time t}}{\text{Total population at time t}}
  • Prevalence is affected by both incidence and duration (longer duration can raise prevalence).
• When are cross-sectional studies used?
  • Describe prevalence and distribution in a population.
  • Compare prevalence between groups (e.g., age groups).
  • Generate hypotheses.
  • Plan or evaluate health services and delivery.
• What are cross-sectional studies good for?
  • Assess multiple exposures and multiple outcomes.
  • Quick and relatively inexpensive.
  • Descriptive and hypothesis-generating.
• What are their limitations?
  • Temporal sequencing is unclear -> cannot establish causation or the direction of associations.
  • Measure prevalence, not incidence.
  • Not ideal for rare outcomes or exposures.
  • Not good for variable or transient exposures/outcomes.
• Examples from slides
  • New Zealand Health Survey; Census of Populations and Dwellings; Youth 2000; Youth19.
• How to interpret associations in a cross-sectional study?
  • Snapshot of exposure–outcome status; associations may be due to reverse causation or confounding.
• Classic 2x2 example (conceptual)
  • 2x2 table framework used to compute prevalences within exposure groups; e.g., BMI categories vs knee pain.
  • Prevalence in a group = proportion with the outcome within that group.
• Hypothesis generation in cross-sectional studies
  • Example: Which factors are associated with low back pain among nurses? Demographic, work physical, work organizational, psychosocial, etc. (identify multiple potential factors for future testing).
• Strengths and limitations recap
  • Strengths: multiple exposures/outcomes, rapid, inexpensive, good for prevalence.
  • Limitations: no temporal sequence, cannot infer causation, not ideal for rare or transient factors.
• GATE frame for critical appraisal (visual tool)
  • Components: Source, Population, Exposed Group, Comparison Group, Exposure/Comparison, Outcome, Time, Sample.
  • Purpose: facilitates structured assessment of bias, relevance, and applicability.
• Quick recap: key formulas and concepts
  • Prevalence measures the proportion of people with the disease at a point in time.
  • Prevalence = \frac{\text{Number with disease at time t}}{\text{Total population at time t}}.
  • Prevalence is influenced by incidence and duration; cross-sectional studies capture prevalence, not incidence.

Ecological studies

• What are ecological studies?
  • Also called correlational studies.
  • Compare exposures and outcomes across GROUPS (populations) rather than individuals.
• What are they used for?
  • Compare populations or regions.
  • Assess population-level factors and generate population-level hypotheses.
  • Data are often routinely collected; may be easier and cheaper.
• How do ecological studies differ from individual-level studies?
  • Ecological: exposure status and outcome are assessed at the group level.
  • Individual-level studies assess exposure and outcome within individuals.
• What are ecological studies good for?
  • Population-level insights; exploring hypotheses about broad drivers of health.
• Examples from slides
  • Kennedy, Kawachi, Prothrow-Stith (1996): Income distribution and mortality (cross-sectional ecological study).
  • Doll (1955): Ecology of lung cancer and cigarette consumption across countries.
  • Breslin, Smith, Dunn (2007): Regional variation in work injuries and regional characteristics.
• Limitations of ecological studies
  • Ecological fallacy: ascribing group-level characteristics to individuals.
  • Cannot control for confounding; cannot establish causation.
• Why use ecological studies?
  • When the research question focuses on population-level exposures or when data are routinely collected and easy to obtain.
  • Useful for generating hypotheses and informing policy at a population level.
• Recap: key takeaways
  • Ecological studies use group-level data; beware ecological fallacy.
  • They are useful for population-level questions, often inexpensive and based on readily available data, but limited for causal inference.
• Quick comparison recap
  • Cross-sectional: single timepoint, individual-level data, measures prevalence, snapshot associations.
  • Ecological: group-level data, population-wide comparisons, ecological fallacy risk, limited causal inference.