INTRODUCTION:
Observational studies play a central role in public health research, particularly in the evaluation of population health, social determinants, and health inequities across diverse social, economic, and epidemiological contexts. In settings marked by structural inequalities and cross-national variability, observational evidence is often a primary source for informing public health policies and interventions. Meta-analysis is a statistical technique used to combine and synthesize results from individual studies with clinical and methodological similarities and can be effectively applied to observational designs. However, observational meta-analyses are inherently characterized by substantial heterogeneity, reflecting real-world differences between populations, health systems, and contexts rather than methodological flaws alone.

OBJECTIVE:
To analyze heterogeneity in observational meta-analyses and discuss its contribution to epidemiological knowledge, with emphasis on implications for health equity and population-level evidence.

METHODS:
This theoretical essay adopts a reflective methodological approach to examine strategies for addressing heterogeneity in observational meta-analyses, based on procedures developed and applied in three observational studies, focusing on statistical and contextual approaches to heterogeneity assessment.

RESULTS:
Statistical assessments using Cochran’s Q test and the Higgins and Thompson I² statistic indicated significant heterogeneity (p<0.05), with moderate to high magnitude across studies. To address this variability, subgroup analyses based on population characteristics and study contexts were conducted, alongside random-effects models. Meta-regression analyses estimated the influence of covariates and contextual factors on effect sizes, allowing a more nuanced interpretation of variability across populations.

CONCLUSIONS:
While statistical tests are essential for identifying heterogeneity in observational meta-analyses, analyses should not be restricted to these measures alone. Heterogeneity should be interpreted as an expression of epidemiological and socioeconomic contexts within and between countries. Incorporating contextual and methodological approaches strengthens meta-analyses by producing more reliable and equitable evidence, avoiding overly generalized conclusions that may obscure health inequalities and compromise ethical public health decision-making.