Article type
Abstract
Background
Life expectancy is on the rise across all countries with older adults experiencing increasing health and social disparities due to systems that are not equipped to provide the health and social care they need. Decision-makers need better evidence to inform health equity considerations, but this evidence is difficult to identify. Evidence and gap maps are visual and interactive tools that can be used in this field to make research evidence more discoverable.
Objectives
This project aims to assess methods of mapping equity in evidence and gap maps on ageing.
Methods
We assessed how equity is coded in four evidence and gap maps on ageing as description of population characteristics, description of outcomes related to equity, analysis to assess potential differences in effects across populations, and applicability of findings to specific populations.
Results
Population characteristics across sex and age was commonly described in ≥70% of included studies in all four evidence and gap maps but other equity-related characteristics (e.g. place of residence, race, occupation, education, socioeconomic status) were hardly described. LGBTQ+ communities were considered in only one study included in one of the maps.
Equity-related outcomes (e.g. digital divide, social cohesion, social capital) were considered in three evidence and gap maps, but only social cohesion and social capital were reported in <2% of included studies in one map.
The percentage of included studies across the four maps that analyzed differential effects of interventions across sex/gender ranged from 0.2% to 6.8%. Differential effects across age were analyzed in 1.4% and 5.1% of included studies in two maps respectively. Differential effects were not analyzed for other equity factors such as place of residence, occupation.
Applicability of findings to specific populations such as the oldest old (>80 years old) or LGBTQ+ communities was not possible in any of the evidence maps as very few studies included these populations.
Conclusions
In our limited sample, we demonstrated that equity-related concerns were rarely considered in evidence mapping. If decision-making requires the application of an equity lens to evidence mapping, then better reporting will be indispensable for making the evidence accessible, if our findings hold true.
Life expectancy is on the rise across all countries with older adults experiencing increasing health and social disparities due to systems that are not equipped to provide the health and social care they need. Decision-makers need better evidence to inform health equity considerations, but this evidence is difficult to identify. Evidence and gap maps are visual and interactive tools that can be used in this field to make research evidence more discoverable.
Objectives
This project aims to assess methods of mapping equity in evidence and gap maps on ageing.
Methods
We assessed how equity is coded in four evidence and gap maps on ageing as description of population characteristics, description of outcomes related to equity, analysis to assess potential differences in effects across populations, and applicability of findings to specific populations.
Results
Population characteristics across sex and age was commonly described in ≥70% of included studies in all four evidence and gap maps but other equity-related characteristics (e.g. place of residence, race, occupation, education, socioeconomic status) were hardly described. LGBTQ+ communities were considered in only one study included in one of the maps.
Equity-related outcomes (e.g. digital divide, social cohesion, social capital) were considered in three evidence and gap maps, but only social cohesion and social capital were reported in <2% of included studies in one map.
The percentage of included studies across the four maps that analyzed differential effects of interventions across sex/gender ranged from 0.2% to 6.8%. Differential effects across age were analyzed in 1.4% and 5.1% of included studies in two maps respectively. Differential effects were not analyzed for other equity factors such as place of residence, occupation.
Applicability of findings to specific populations such as the oldest old (>80 years old) or LGBTQ+ communities was not possible in any of the evidence maps as very few studies included these populations.
Conclusions
In our limited sample, we demonstrated that equity-related concerns were rarely considered in evidence mapping. If decision-making requires the application of an equity lens to evidence mapping, then better reporting will be indispensable for making the evidence accessible, if our findings hold true.