How Equity-Oriented Health Care Affects Health: Key Mechanisms and Implications for Primary Health Care Practice and Policy

Policy Points A consensus regarding the need to orient health systems to address inequities is emerging, with much of this discussion targeting population health interventions and indicators. We know less about applying these approaches to primary health care. This study empirically demonstrates that providing more equity-oriented health care (EOHC) in primary health care, including trauma- and violence-informed, culturally safe, and contextually tailored care, predicts improved health outcomes across time for people living in marginalizing conditions. This is achieved by enhancing patients’ comfort and confidence in their care and their own confidence in preventing and managing health problems. This promising new evidence suggests that equity-oriented interventions at the point of care can begin to shift inequities in health outcomes for those with the greatest need. Context: Significant attention has been directed toward addressing health inequities at the population health and systems levels, yet little progress has been made in identifying approaches to reduce health inequities through clinical care, particularly in a primary health care context. Although the provision of equity-oriented health care (EOHC) is widely assumed to lead to improvements in patients’ health outcomes, little empirical evidence supports this claim. To remedy this, we tested whether more EOHC predicts more positive patient health outcomes and identified selected mediators of this relationship. Methods: Our analysis uses longitudinal data from 395 patients recruited from 4 primary health care clinics serving people living in marginalizing conditions. The participants completed 4 structured interviews composed of self-report measures and survey questions over a 2-year period. Using path analysis techniques, we tested a hypothesized model of the process through which patients’ perceptions of EOHC led to improvements in self-reported health outcomes (quality of life, chronic pain disability, and posttraumatic stress [PTSD] and depressive symptoms), including particular covariates of health outcomes (age, gender, financial strain, experiences of discrimination). Findings: Over a 24-month period, higher levels of EOHC predicted greater patient comfort and confidence in the health care patients received, leading to increased confidence to prevent and manage their health problems, which, in turn, improved health outcomes (depressive symptoms, PTSD symptoms, chronic pain, and quality of life). In addition, financial strain and experiences of discrimination had significant negative effects on all health outcomes. Conclusions: This study is among the first to demonstrate empirically that providing more EOHC predicts better patient health outcomes over time. At a policy level, this research supports investments in equity-focused organizational and provider-level processes in primary health care as a means of improving patients’ health, particularly for those living in marginalizing conditions. Whether these results are robust in different patient groups and across a broader range of health care contexts requires further study

The State of Research on Racial and Ethnic Discrimination in the Receipt of Health Care

https://ajph.aphapublications.org/doi/pdf/10.2105/AJPH.2012.30077

Sources of Interactional Problems in a Survey of Racial/Ethnic Discrimination

Cross-cultural variability in respondent processing of survey questions may bias results from multiethnic samples. We analyzed behavior codes, which identify difficulties in the interactions of respondents and interviewers, from a discrimination module contained within a field test of the 2007 California Health Interview Survey. In all, 553 (English) telephone interviews yielded 13,999 interactions involving 22 items. Multilevel logistic regression modeling revealed that respondent age and several item characteristics (response format, customized questions, length, and first item with new response format), but not race/ethnicity, were associated with interactional problems. These findings suggest that item function within a multi-cultural, albeit English language, survey may be largely influenced by question features, as opposed to respondent characteristics such as race/ethnicity

A healthy mistrust: how worldview relates to attitudes about breast cancer screening in a cross-sectional survey of low-income women

<p>Abstract</p> <p>Background</p> <p>Perceived racial discrimination is one factor which may discourage ethnic minorities from using healthcare. However, existing research only partially explains why some persons do accept health promotion messages and use preventive care, while others do not. This analysis explores 1) the psychosocial characteristics of those, within disadvantaged groups, who identify their previous experiences as racially discriminatory, 2) the extent to which perceived racism is associated with broader perspectives on societal racism and powerlessness, and 3) how these views relate to disadvantaged groups' expectation of mistreatment in healthcare, feelings of mistrust, and motivation to use care.</p> <p>Methods</p> <p>Using survey data from 576 African-American women, we explored the prevalence and predictors of beliefs and experiences related to social disengagement, racial discrimination, desired and actual racial concordance with medical providers, and fear of medical research. We then used both sociodemographic characteristics, and experiences and attitudes about disadvantage, to model respondents' scores on an index of personal motivation to receive breast cancer screening, measuring screening knowledge, rejection of fatalistic explanatory models of cancer, and belief in early detection, and in collaborative models of patient-provider responsibility.</p> <p>Results</p> <p>Age was associated with lower motivation to screen, as were depressive symptoms, anomie, and fear of medical research. Motivation was low among those more comfortable with African-American providers, regardless of current provider race. However, greater awareness of societal racism positively predicted motivation, as did talking to others when experiencing discrimination. Talking was most useful for women with depressive symptoms.</p> <p>Conclusion</p> <p>Supporting the Durkheimian concepts of both anomic and altruistic suicide, both disengagement (depression, anomie, vulnerability to victimization, and discomfort with non-Black physicians) as well as over-acceptance (low awareness of discrimination in society) predict poor health maintenance attitudes in disadvantaged women. Women who recognize their connection to other African-American women, and who talk about negative experiences, appear most motivated to protect their health.</p

The Australian Racism, Acceptance, and Cultural-Ethnocentrism Scale (RACES): item response theory findings

BACKGROUND: Racism and associated discrimination are pervasive and persistent challenges with multiple cumulative deleterious effects contributing to inequities in various health outcomes. Globally, research over the past decade has shown consistent associations between racism and negative health concerns. Such research confirms that race endures as one of the strongest predictors of poor health. Due to the lack of validated Australian measures of racist attitudes, RACES (Racism, Acceptance, and Cultural-Ethnocentrism Scale) was developed. METHODS: Here, we examine RACES’ psychometric properties, including the latent structure, utilising Item Response Theory (IRT). Unidimensional and Multidimensional Rating Scale Model (RSM) Rasch analyses were utilised with 296 Victorian primary school students and 182 adolescents and 220 adults from the Australian community. RESULTS: RACES was demonstrated to be a robust 24-item three-dimensional scale of Accepting Attitudes (12 items), Racist Attitudes (8 items), and Ethnocentric Attitudes (4 items). RSM Rasch analyses provide strong support for the instrument as a robust measure of racist attitudes in the Australian context, and for the overall factorial and construct validity of RACES across primary school children, adolescents, and adults. CONCLUSIONS: RACES provides a reliable and valid measure that can be utilised across the lifespan to evaluate attitudes towards all racial, ethnic, cultural, and religious groups. A core function of RACES is to assess the effectiveness of interventions to reduce community levels of racism and in turn inequities in health outcomes within Australia. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12939-016-0338-4) contains supplementary material, which is available to authorized users

Racism as a determinant of health: a systematic review and meta-analysis

Despite a growing body of epidemiological evidence in recent years documenting the health impacts of racism, the cumulative evidence base has yet to be synthesized in a comprehensive meta-analysis focused specifically on racism as a determinant of health. This meta-analysis reviewed the literature focusing on the relationship between reported racism and mental and physical health outcomes. Data from 293 studies reported in 333 articles published between 1983 and 2013, and conducted predominately in the U.S., were analysed using random effects models and mean weighted effect sizes. Racism was associated with poorer mental health (negative mental health: r = -.23, 95% CI [-.24,-.21], k = 227; positive mental health: r = -.13, 95% CI [-.16,-.10], k = 113), including depression, anxiety, psychological stress and various other outcomes. Racism was also associated with poorer general health (r = -.13 (95% CI [-.18,-.09], k = 30), and poorer physical health (r = -.09, 95% CI [-.12,-.06], k = 50). Moderation effects were found for some outcomes with regard to study and exposure characteristics. Effect sizes of racism on mental health were stronger in cross-sectional compared with longitudinal data and in non-representative samples compared with representative samples. Age, sex, birthplace and education level did not moderate the effects of racism on health. Ethnicity significantly moderated the effect of racism on negative mental health and physical health: the association between racism and negative mental health was significantly stronger for Asian American and Latino(a) American participants compared with African American participants, and the association between racism and physical health was significantly stronger for Latino(a) American participants compared with African American participants.<br /

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic