Article type
Year
Abstract
Background:
Identification of social gradients is necessary for the development of efficient public health strategies to address health inequities. However isolating the effect of social disadvantage from other confounding factors is not straightforward, and may result in missed or misleading effects.
Objectives:
1. To describe a method of analysis using causal pathways that may reduce bias in the estimation of factors of social disadvantage;
2. To provide a new checklist for assessing the suitability of studies in an equity-based systematic review.
Methods:
We searched for studies that reported kidney disease health outcomes (access to specialist care, disease progression, cardiovascular events/mortality and all-cause mortality) by one or more of the Campbell and Cochrane Equity Methods Group, that acknowledged factors of social disadvantage. Causal pathways were considered to assess whether the reported estimates from the multivariable regression models are unbiased estimates of the total effect of these factors on the health outcomes listed above. We created a new checklist for assessing bias that categorises the suitability of studies into two groups: those with moderate to good suitability and those with low suitability (attached figure). Synthesis of results involved presenting factors of disadvantage on a novel bubble graph according to the suitability of analysis and presence of a social gradient.
Results:
We identified 50 studies representing 8.6 million people from 10 countries that reported health outcomes in chronic kidney disease by one or more factor of disadvantage. Many of the studies, in particular those reporting effects by gender and ethnicity over-adjusted for risk factors and comorbidities likely to be on the causal pathway of disadvantage for these health outcomes.
Conclusions:
Consideration of causal pathways may provide an improvement to the traditional framework for developing and assessing multivariable models.
Identification of social gradients is necessary for the development of efficient public health strategies to address health inequities. However isolating the effect of social disadvantage from other confounding factors is not straightforward, and may result in missed or misleading effects.
Objectives:
1. To describe a method of analysis using causal pathways that may reduce bias in the estimation of factors of social disadvantage;
2. To provide a new checklist for assessing the suitability of studies in an equity-based systematic review.
Methods:
We searched for studies that reported kidney disease health outcomes (access to specialist care, disease progression, cardiovascular events/mortality and all-cause mortality) by one or more of the Campbell and Cochrane Equity Methods Group, that acknowledged factors of social disadvantage. Causal pathways were considered to assess whether the reported estimates from the multivariable regression models are unbiased estimates of the total effect of these factors on the health outcomes listed above. We created a new checklist for assessing bias that categorises the suitability of studies into two groups: those with moderate to good suitability and those with low suitability (attached figure). Synthesis of results involved presenting factors of disadvantage on a novel bubble graph according to the suitability of analysis and presence of a social gradient.
Results:
We identified 50 studies representing 8.6 million people from 10 countries that reported health outcomes in chronic kidney disease by one or more factor of disadvantage. Many of the studies, in particular those reporting effects by gender and ethnicity over-adjusted for risk factors and comorbidities likely to be on the causal pathway of disadvantage for these health outcomes.
Conclusions:
Consideration of causal pathways may provide an improvement to the traditional framework for developing and assessing multivariable models.