Marginal and Conditional Confounding Using Logits.

This article presents two ways of quantifying confounding using logistic response models for binary outcomes. Drawing on the distinction between marginal and conditional odds ratios in statistics, we define two corresponding measures of confounding (marginal and conditional) that can be recovered from a simple standardization approach. We investigate when marginal and conditional confounding may differ, outline why the method by Karlson, Holm, and Breen recovers conditional confounding under a "no interaction"-assumption, and suggest that researchers may measure marginal confounding by using inverse probability weighting.

Is austerity a cause of slower improvements in mortality in high-income countries? A panel analysis.

Background: The rate of improvement in mortality slowed across many high-income countries after 2010. Following the 2007-08 financial crisis, macroeconomic policy was dominated by austerity as countries attempted to address perceived problems of growing state debt and government budget deficits. This study estimates the impact of austerity on mortality trends for 37 high-income countries between 2000 and 2019.

Does persistent precarious employment affect health outcomes among working age adults? A systematic review and meta-analysis.

Objective: To evaluate the impact of persistent precarious employment (lasting 12+ months) on the health of working age adults, compared with more stable employment. Persistent precarity reflects a shift towards less secure forms of employment and may be particularly important for health.

Methods: Nine databases were systematically searched to identify quantitative studies that assessed the relationship between persistent precarious employment and health outcomes.