Interpreting time-related trends in effect estimates

Area of Science:

• Epidemiology
• Biostatistics
• Health Research Methodology

Background:

• Apparent time trends in effect measures can be misleading.
• These trends may arise from various confounding factors unrelated to the actual effect.
• Time itself does not cause changes; underlying factors do.

Purpose of the Study:

• To review and elucidate the diverse sources of apparent time trends in effect measures.
• To emphasize the importance of identifying these sources for accurate scientific interpretation.
• To discuss how different explanations align with age, cohort, or period effects.

Main Methods:

• Literature review of epidemiological and statistical concepts.
• Analysis of how changes in covariate distributions, background rates, exposure, measurement quality, and selection factors influence effect trends.
• Examination of the interplay between effect measures and changing background incidence.
• Discussion of age, cohort, and period phenomena in trend analysis.

Main Results:

• Apparent time trends in effect are attributed to changes in covariate distributions, background rates, exposure, measurement quality, or selection factors.
• The choice of effect measure is critical when background incidence is changing.
• Evidence for age-, cohort-, or period-related phenomena helps evaluate trend explanations.
• Short-duration studies require strong assumptions to attribute trends to specific axes (age, cohort, or time).

Conclusions:

• Apparent time trends in effect measures necessitate careful examination of underlying sources.
• Accurate interpretation depends on accounting for changes in study parameters and background rates.
• The choice of analytical axis (age, cohort, period) should be guided by the plausibility of different explanations.
• Methodological rigor is essential, especially in studies with limited duration relative to observed trends.