# Exploring the Influence of Social Class and Sex on Self-Reported Health: Insights from a Representative Population-Based Study

## TL;DR

This study explores how social class and sex influence self-reported health in Spain, revealing socioeconomic factors have lasting effects.

## Contribution

The study introduces a novel use of DAGs to identify essential covariates and clarify the direct effects of social class and sex on health.

## Key findings

- Social class shows a gradient effect on self-reported health, with lower classes reporting worse health.
- Sex disparities in health diminish after adjusting for health-related variables.
- Directed acyclic graphs help identify key covariates to control confounding in health disparities.

## Abstract

This study investigates the intricate interplay between social class, sex, and self-reported health (SRH) using data from the European Health Survey of Spain 2020 (EESE2020). Employing a cross-sectional design and a representative sample of 22,072 individuals, the analysis explores the persistence of disparities after adjusting for covariates, focusing on health-related variables. The study employs logistic regression models and directed acyclic graphs (DAGs) to delineate the direct effects of social class and sex on SRH, identifying a minimum adjustment set to control for confounding variables. Results reveal a gradient effect of social class on SRH, emphasizing the enduring impact of socioeconomic factors. Sex-based disparities in SRH diminish after considering additional health-related variables, highlighting the importance of a holistic approach. DAGs serve as transparent tools in disentangling complex relationships, guiding the identification of essential covariates. The study concludes that addressing health inequalities requires comprehensive strategies considering both individual health behaviours and socio-economic contexts. While recognizing limitations, such as the cross-sectional design, the findings contribute to a nuanced understanding of health disparities, informing evidence-based interventions and policies for a more equitable healthcare system.