Contextualizing Educational Disparities in Health: Variations by Race/Ethnicity, Nativity, and County-Level Characteristics

Educational disparities in health are well documented, yet the education–health relationship is inconsistent across racial/ethnic and nativity groups. These inconsistencies may arise from characteristics of the early life environments in which individuals attain their education. We evaluate this possibility by investigating (1) whether educational disparities in cardiometabolic risk vary by race/ethnicity and nativity among Black, Hispanic, and White young adults; (2) the extent to which racial/ethnic-nativity differences in the education–health relationship are contingent on economic, policy, and social characteristics of counties of early life residence; and (3) the county characteristics associated with the best health at higher levels of education for each racial/ethnic-nativity group. Using data from the National Longitudinal Study of Adolescent to Adult Health, we find that Black young adults who achieve high levels of education exhibit worse health across a majority of contexts relative to their White and Hispanic counterparts. Additionally, we observe more favorable health at higher levels of education across almost all contexts for White individuals. For all other racial/ethnic-nativity groups, the relationship between education and health depends on the characteristics of the early life counties of residence. Findings highlight place-based factors that may contribute to the development of racial/ethnic and nativity differences in the education–health relationship among U.S. young adults.

Access to primary healthcare Services in Conflict-Affected Fragile States: a subnational descriptive analysis of educational and wealth disparities in Cameroon, Democratic Republic of Congo, Mali, and Nigeria

Background Measuring and improving equitable access to care is a necessity to achieve universal health coverage. Pre-pandemic estimates showed that most conflict-affected and fragile situations were off-track to meet the Sustainable Development Goals on health and equity by 2030. Yet, there is a paucity of studies examining health inequalities in these settings. This study addresses the literature gap by applying a conflict intensity lens to the analysis of disparities in access to essential Primary Health Care (PHC) services in four conflict-affected fragile states: Cameroon, Democratic Republic of Congo, Mali and Nigeria. Methods For each studied country, disparities in geographic and financial access to care were compared across education and wealth strata in areas with differing levels of conflict intensity. The Demographic Health Survey (DHS) and the Uppsala Conflict Data Program were the main sources of information on access to PHC and conflict events, respectively. To define conflict intensity, household clusters were linked to conflict events within a 50-km distance. A cut-off of more than two conflict-related deaths per 100,000 population was used to differentiate medium or high intensity conflict from no or low intensity conflict. We utilized three measures to assess inequalities: an absolute difference, a concentration index, and a multivariate logistic regression coefficient. Each disparity measure was compared based on the intensity of conflict the year the DHS data was collected. Results We found that PHC access varied across subnational regions in the four countries studied; with more prevalent financial than geographic barriers to care. The magnitude of both educational and wealth disparities in access to care was higher with geographic proximity to medium or high intensity conflict. A higher magnitude of wealth rather than educational disparities was also likely to be observed in the four studied contexts. Meanwhile, only Nigeria showed statistically significant interaction between conflict intensity and educational disparities in access to care. Conclusion Both educational and wealth disparities in access to PHC services can be exacerbated by geographic proximity to organized violence. This paper provides additional evidence that, despite limitations, household surveys can contribute to healthcare assessment in conflict-affected and fragile settings.

Education, Financial Stress, and Trajectory of Mental Health During the COVID-19 Pandemic

In this preregistered study, we examined educational disparities in the trajectory of mental health during the COVID-19 pandemic and whether such educational disparities would be mediated by financial stress associated with the pandemic. Data were drawn from the Love in the Time of COVID project ( N = 2,204; four waves collected between March and June 2020). Results suggested educational disparities in eudaimonic well-being, negative affect, and psychological distress and showed significant associations between lower education and worse mental-health outcomes at baseline. However, education did not amplify mental-health disparities over time and exhibited no associations with the rates of change in mental health. Financial stress mediated the associations between education and mental health at baseline, and there were no temporal variations in the mediation effect. These results highlight persistent educational disparities in mental health, and such educational disparities may be partially explained by financial stress associated with the COVID-19 pandemic.

Effects of the Great Recession on Educational Disparities in Cardiometabolic Health

Background Macroeconomic crises can exaggerate existing educational disparities in health. Few studies, however, have examined whether macroeconomic crises get under the skin to affect educational disparities in health-related biological processes. Purpose This study aimed to examine the effect of the economic recession of 2008 (i.e., Great Recession) on educational disparities in cardiometabolic risk and self-reported psychological distress. Methods Data were drawn from two subsamples of the Midlife in the United States (MIDUS) study: the second wave of the MIDUS sample (pre-recession cohort, N = 985) and the refresher sample (post-recession cohort, N = 863). Educational attainment was categorized into high school education or less, some college, and bachelor’s degree or higher. Outcomes included metabolic syndrome, C-reactive protein, and interleukin-6, as well as self-reported perceived stress, depressive symptoms, and financial distress. Results Results showed that having a bachelor’s degree or higher (compared to having a high school education or less) was more strongly associated with decreased metabolic syndrome symptoms in the post-recession cohort than the pre-recession cohort, above and beyond demographic, health, and behavioral covariates. These findings did not extend to systemic inflammation or psychological distress. Conclusions Our findings suggest that chronic macroeconomic stressors may widen the educational gap in physical health, particularly cardiometabolic health, by modifying biological and anthropometric risk factors implicated in metabolic syndrome.

Access to Primary Healthcare Services in Conflict-Affected Fragile States: A Subnational Descriptive Analysis of Educational and Wealth Disparities in Cameroon, Democratic Republic of Congo, Mali, and Nigeria

Background Measuring and improving equitable access to care is a necessity to achieve universal health coverage. Pre-pandemic estimates showed that most conflict-affected and fragile situations were off-track to meet the Sustainable Development Goals on health and equity by 2030. Yet, there is a paucity of studies examining health inequalities in these settings. This study addresses the literature gap by applying a conflict intensity lens to the analysis of disparities in access to essential Primary Health care (PHC) services in four conflict-affected fragile states: Cameroon, Democratic Republic of Congo, Mali and Nigeria. Methods For each studied country, disparities in geographic and financial access to care were compared across education and wealth strata in areas with differing levels of conflict intensity. The Demographic Health Survey (DHS) and the Uppsala Conflict Data Program were the main sources of information on access to PHC and conflict events, respectively. To define conflict intensity, household clusters were linked to conflict events within a 50-km distance. A cut-off of more than two conflict-related deaths per 100,000 population was used to differentiate medium or high intensity conflict from no or low intensity conflict. We utilized three measures to assess inequalities: an absolute difference, a concentration index, and a multivariate logistic regression coefficient. Each disparity measure was compared based on the intensity of conflict the year the DHS data was collected. Results We found that PHC access varied across subnational regions in the four countries studied; with more prevalent financial than geographic barriers to care. The magnitude of both educational and wealth disparities in access to care was higher with geographic proximity to medium or high intensity conflict. A higher magnitude of wealth rather than educational disparities was also likely to be observed in the four studied contexts. Meanwhile, we only found few examples of statistical interaction between conflict intensity and either wealth or educational disparities in access to care. Conclusion Both educational and wealth disparities in access to PHC services can be exacerbated by geographic proximity to organized violence. This paper provides additional evidence that, despite limitations, household surveys can contribute to healthcare assessment in conflict-affected and fragile settings.

Leading cancers contributing to educational disparities in cancer mortality in the US, 2017

Purpose To inform prevention efforts, we sought to determine which cancer types contribute the most to cancer mortality disparities by individual-level education using national death certificate data for 2017. Methods Information on all US deaths occurring in 2017 among 25–84-year-olds was ascertained from national death certificate data, which include cause of death and educational attainment. Education was classified as high school or less (≤ 12 years), some college or diploma (13–15 years), and Bachelor's degree or higher (≥ 16 years). Cancer mortality rate differences (RD) were calculated by subtracting age-adjusted mortality rates (AMR) among those with ≥ 16 years of education from AMR among those with ≤ 12 years. Results The cancer mortality rate difference between those with a Bachelor's degree or more vs. high school or less education was 72 deaths per 100,000 person-years. Lung cancer deaths account for over half (53%) of the RD for cancer mortality by education in the US. Conclusion Efforts to reduce smoking, particularly among persons with less education, would contribute substantially to reducing educational disparities in lung cancer and overall cancer mortality.