Assessment of health equity consideration in masking/PPE policies to contain COVID-19 using PROGRESS-plus framework: a systematic review

Analysis of social determinants of health and individual factors found in health equity frameworks: Applications to injury research

INTRODUCTION

This research evaluated existing health equity frameworks as they relate to social determinants of health (SDOHs) and individual factors that may impact injury outcomes and identify gaps in coverage using the Healthy People (HP) 2030 key domains.

METHODS

The study used a list of health equity frameworks sourced from previous literature. SDOHs and individual factors from each framework were identified and categorized into the Healthy People 2030 domains. Five injury topic areas were used as examples for how SDOHs and individual factors can be compared to injury topic-specific health disparities to identify health equity frameworks to apply to injury research.

RESULTS

The study identified 59 SDOHs and individual factors from the list of 33 health equity frameworks. The number of SDOHs and individual factors identified varied by Healthy People 2030 domain: Neighborhood and Built Environment contained 16 (27.1%) SDOHs and individual actors, Social and Community Context contained 22 (37.3%), Economic Stability contained 10 (16.9%), Healthcare Access and Quality contained 10 (16.9%), and Education Access and Quality contained one (1.7%). Twenty-three (39.0%) SDOHs/individual factors related to traumatic brain injury, thirteen (22.0%) related to motor vehicle crashes and suicide, 11 (18.6%) related to drowning and older adult falls. Eight frameworks (24.2%) covered all HP 2030 key domains and may be applicable to injury topics.

CONCLUSIONS

Incorporating health equity into research is critical. Health equity frameworks can provide a way to systematically incorporate health equity into research. The findings from this study may be useful to health equity research by providing a resource to injury and other public health fields.

PRACTICAL APPLICATIONS

Health equity frameworks are a practical tool to guide injury research, translation, evaluation, and program implementation. The findings from this study can be used to guide the application of health equity frameworks in injury research for specific topic areas.

The hidden inequality: the disparities in the quality of daily use masks associated with family economic status

Wearing high-quality masks plays a critical role in reducing COVID-19 transmission. However, no study has investigated socioeconomic inequality in the quality of masks. Addressing this gap, this paper explored the relationships between mask's quality and family economic status. The cross-sectional survey was conducted in two Chinese universities by distributing structured questionnaires to assess participants' characteristics including family economic status, and meanwhile collecting their masks to evaluate the quality by measuring particle filtration efficiency. The valid responses were obtained from 912 students with mean age of 19.556 ± 1.453  years and were analyzed by using fractional or binary logistic regression. Three main findings were presented. First, inequality existed in the quality of masks. 36.07% of students were using unqualified masks with average filtration efficiency of 0.795 ± 0.119, which was much lower than China's national standard (0.9). Of those masks with identified production date, 11.43% were manufactured during COVID-19 outbreak when market was flooded with counterfeit production, and thus were of poor quality with average filtration efficiency of 0.819 ± 0.152. Second, better family economic status was associated with better masks' filtration efficiency and greater probability of using qualified masks. Third, students with better family economic status tend to use masks with individual packaging, and unique patterns and special designs, which may lead to inequality on a psychological level. Our analysis reveals the hidden socioeconomic inequality that exist behind cheap masks. In facing the challenges of future emerging infectious diseases, it is important to address the inequity to ensure equal access to affordable qualified personal protection equipment.

The digital rainbow: Digital determinants of health inequities

The widely used socioecological rainbow model from Dahlgren and Whitehead specifies determinants of health inequity on multiple hierarchical levels and suggests that these determinants may interact both within and between levels. At the time of its inception, digital determinants only played a minor role in tackling inequities in public health and were therefore not specifically considered. This has dramatically changed: From today's perspective, health inequities increasingly depend on digital determinants. In this article, we suggest adapting the Dahlgren-Whitehead model to reflect these developments. We propose a model that allows formulating testable hypotheses, interpreting research findings, and developing policy implications against the background of the global spread of digital technologies. This may facilitate the development of a new line of research and logic models for public health interventions in the digital age. Using the COVID-19 pandemic as a case study, we illustrate how the digitization of all aspects of life affects the different levels of determinants of health inequities in the Dahlgren-Whitehead model. In doing so, we deliberately argue for not introducing a separate digital sphere in its own right, but for understanding digitization as a phenomenon that permeates all levels of determinants of health inequities. As a result, we present a digital rainbow model that integrates Dahlgren and Whitehead's 1991 model with digital environments to identify current health promotion and research issues without changing the rainbow model's initial structure.

Health equity guiding frameworks and indices in injury: A review of the literature

BACKGROUND

In early 2021, CDC released the CORE Health Equity Strategy, which resolves to integrate a comprehensive health equity approach to the work of the Agency. One priority of the Injury Center's Division of Injury Prevention is to move health equity research in injury forward. The purpose of this research is to perform an initial exploration of health equity guiding frameworks and indices to better understand which of these has been applied to injury research topics.

METHODS

A PubMed and CINAHL search of meta-analysis and systematic review articles was conducted from January 1998 through April 2022. Articles of any type and additional frameworks/indices were also identified from staff knowledge of the literature. Books were also considered, where accessible. The following areas were reviewed for each resource: population addressed, guiding framework/index, other health equity variables, gaps identified, and whether the articles addressed an injury topic.

FINDINGS

The PubMed/CINAHL search produced 230 articles, and an additional 29 articles and 8 books were added from previous knowledge of the literature, resulting in a total of 267 resources for review. There were 60 frameworks/indices compiled that were relevant to health equity. Out of all the resources, three reported on an injury topic and used the PROGRESS-Plus framework, the WHO Social Determinants of Health Conceptual Framework, and a social-ecological framework.

CONCLUSIONS

This study found there were many frameworks/indices for measuring health equity; however, there were few injury-related meta-analysis and systematic review articles. Some frameworks/indices may be more appropriate than others for measuring health equity in injury topic areas, depending on which social determinants of health (SDOHs) they address.

PRACTICAL APPLICATIONS

Measuring health equity in injury and other public health research areas can help build a foundation of evidence. Moving forward, injury researchers can consider the frameworks/indices identified through this study in their health equity injury research.

The influence of democracy, governance and government policies on the COVID-19 pandemic mortality

The paper analyses the determinants of mortality during the Corona pandemic. In a first step, possible causes are subjected to a global comparison.The focus is on political, institutional, economic, demographic and health policy factors. It is shown that, contrary to the assumption, democratic countries have a higher Covid-19 mortality. In a second step, the developed democracies are then analysed to explain this puzzle. Here, more detailed information is used than in the global comparison. It turns out that, measured by the Oxford Stringency Index, government action has been largely unsuccessful. Also, the party-political composition of the government does not play a role.The most important factors are a country's governance structures, the level of corona incidence, a country's burden of high-risk patients and its health system. In addition, cultural factors and the vaccination rate seem to have an influence on mortality.