Lower stroke mortality among Hispanics: an exploration of potential methodological confounders

Critical analyses of Latina mortality: disentangling the heterogeneity of ethnic origin, place, nativity, race, and socioeconomic status

Despite the significant body of research on social determinants of health (SDH) and mortality, limited knowledge is available on the epidemiology of aggregated Latino health overall, and by women and subgroups. In population health studies, U.S. Latinos often are considered a monolithic population and presented as an aggregate, obscuring the diversity and variations within and across Latino subgroups, contributing to missed opportunities to identify SDH of health outcomes, and limiting the understanding of health differences. Given diverse environmental, racial, class, and geographic factors, a specific focus on women facilitates a more in-depth view of health disparities. This paper provides a scoping review of current gaps in research that assesses the relationships between SDH and mortality rates for the five leading causes of chronic-disease related deaths among Latinas by ethnic origin, place, race, and SES. We analyzed 2020 national mortality statistics from the CDC WONDER Online database jointly with reviews of empirical articles on Latina health, employing the EBSCOhost MEDLINE databases. These findings challenge the phenomenon of the Hispanic paradox that identified Latinos as a relatively healthy population compared to non-Hispanic White populations despite their lower economic status. The findings confirm that prior research on Latino women had methodological limitations due to the exclusion of SDH and an overemphasis on culturalist perspectives, while overlooking the critical role of socioeconomic impacts on health. Findings indicate major knowledge gaps in Latina mortality by SDH and subgroups that may undermine surveillance efforts and treatment efficacy. We offer forward-looking recommendations to assure the inclusion of key SDH associated with Latina mortality by subgroup as essential to inform future studies, intervention programs, and health policy.

The Effects of Body Mass Index on In-hospital mortality following first ischemic or hemorrhagic stroke events: Does the "obesity paradox" apply?

Background

While it is widely held that obesity is a risk factor for stroke, its role in mortality after stroke is less understood. We aim to examine effects of Body Mass Index (BMI) on in-hospital mortality after non-subarachnoid, subarachnoid, and ischemic stroke.

Methods

Retrospective cohort study. Patients aged ≥18 years, who were hospitalized in Florida hospitals between 2008 and 2012 with a diagnosis of first-time stroke as reported by the Agency for Health Care Administration (AHCA). The main independent variable was BMI category, which was divided into non-overweight/non-obese, obese, and morbidly obese. The primary outcome was the adjusted odds ratio (aOR) for in-hospital mortality for subarachnoid and non-subarachnoid hemorrhagic stroke, and ischemic stroke. Logistic regression modeling was utilized to examine the association between each BMI category and in-hospital mortality, while controlling for several potential confounders. This study was reported in line with the STROCSS criteria.

Results

Of the 333,367 patients included in the database, 150,153 (45.0%) patients met inclusion criteria. After adjusting for age, gender, ethnicity and other possible confounders, obese patients were 21% less likely to die during their hospitalization following a first ischemic stroke (0.79 aOR, 0.69–0.92, 95% CI, p = 0.002), and 32% less likely following a first non-subarachnoid hemorrhage (0.68 aOR, 0.57–0.82, 95% CI, p = 0.0001) compared to non-overweight/non-obese counterparts.

Conclusion

Obese patients are less likely to die during hospitalization following first-time non-subarachnoid hemorrhage and ischemic stroke than non-overweight/non-obese patients. These findings support the “obesity paradox” concept, though more research is needed for recurrent stroke patients.

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Obese patients were less likely to die in the hospital after first-time ischemic stroke and non-subarachnoid hemorrhage compared to non-overweight/non-obese patients.

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Future studies should further Investigate the “obesity paradox” in relation to BMI classifications and hemorrhagic stroke.

Circulating Cytokines and Coronavirus Disease: A Bi-Directional Mendelian Randomization Study

BACKGROUND

Immune system functioning is relevant to vulnerability to coronavirus disease (COVID-19). Cytokines are important to immunity. To further elucidate the role of the immune system in COVID-19, we used Mendelian randomization (MR) to assess comprehensively and bi-directionally the role of cytokines in COVID-19.

METHODS

We assessed primarily whether genetically different levels of 41 cytokines affected risk of any COVID-19 (laboratory confirmed, physician confirmed or self-reported, 36,590 cases, 1,668,938 controls), and conversely if genetic risk of liability to any COVID-19 affected these cytokines (n ≤ 8293) using the most recent genome-wide association studies. We obtained inverse variance weighting (IVW) estimates, conducted sensitivity analyses and used a Benjamini-Hochberg correction to account for multiple comparisons. We also assessed whether any findings were evident for hospitalized COVID-19 (hospitalized laboratory confirmed, 12,888 cases, 1,295,966 controls).

RESULTS

Macrophage inflammatory protein-1β (MIP1b; more commonly known as Chemokine (C-C motif) ligands 4 (CCL4) was inversely associated with COVID-19 [odds ratio (OR) 0.97 per SD, 95% confidence interval (CI) 0.96-0.99] but not after adjustment for multiple comparisons. This finding replicated for hospitalized COVID-19 (OR 0.93, 95% CI 0.89-0.98). Liability to any COVID-19 was nominally associated with several cytokines, such as granulocyte colony-stimulating factor (GCSF) and hepatocyte growth factor (HGF) but not after correction.

CONCLUSION

A crucial element of immune response to infection (CCL4) was related to COVID-19, whether it is a target of intervention to prevent COVID-19 warrants further investigation.

Reproduction and longevity: A Mendelian randomization study of gonadotropin-releasing hormone and ischemic heart disease

Background

According to well-established evolutionary biology theory there is a trade-off between reproduction and longevity, implying that upregulating the reproductive axis might drive major diseases. We assessed whether the central driver of reproduction gonadotropin-releasing hormone 1 (GnRH1) had a causal effect on the leading cause of global morbidity and mortality, i.e. ischemic heart disease (IHD). As a contrast we similarly examined the role of GnRH2 because it is more a driver of female sexual behavior.

Methods

We applied strong (p-value <5 × 10^-6) and independent genetic predictors of GnRH1 and GnRH2 to an extensively genotyped IHD case (n = 76,014) - control (n = 264,785) study and combined the genetic variant specific Wald estimates using inverse variance weighting (IVW) with multiplicative random effects, and as a sensitivity analysis used weighted median, MR-Egger and MR-PRESSO estimates, and repeated the analysis only using genome wide significant genetic predictors.

Findings

GnRH1, predicted by 11 genetic variants, was positively associated with IHD (IVW odds ratio (OR) 1.04 per effect size, 95% confidence interval (CI) 1.01 to 1.08), but GnRH2, predicted by 15 genetic variants, was not (IVW OR 0.98, 95% CI 0.95 to 1.02). Estimates from sensitivity analysis were similar.

Interpretation

GnRH1 is a potential IHD genetic target. Apart from demonstrating a central tenet of evolutionary biology in humans, our study suggests that existing treatments and environmental factors targeting GnRH1, its drivers or consequences could be re-purposed to prevent and treat IHD. Given, the importance of reproduction to the human species, many such exposures likely exist.

Socioeconomic Status as a Predictor of Mortality in Patients Admitted With Atrial Fibrillation

Lower socioeconomic status (SES) is associated with a higher risk of cardiovascular disease. However, the association between SES and mortality in patients with atrial fibrillation (AF) is not clear. We examined whether SES predicts all-cause mortality in patients hospitalized with AF. This is a retrospective study of patients aged >18 years, admitted with a primary diagnosis of AF to Montefiore Medical Center between 2000 and 2010. Multivariable logistic regression models were used to determine predictors of survival adjusted for age, gender, heart failure, diabetes mellitus, chronic kidney disease, previous myocardial infraction, chronic obstructive pulmonary disease, hypertension, peripheral vascular disease, and SES. SES was determined using the New York City Department of Health Standardized Score (a log composite score of household income, value of housing units, net rental income, household occupations, and educational level). The cohort was divided into quartiles based on SES score, with Q4 the highest and Q1 the lowest SES score. There were 4,503 patients identified with a mean follow up of 4.5 years in the following SES quartiles: Q1 (n = 1,132), Q2 (n = 1,119), Q3 (n = 1,126), and Q4 (n = 1,126). The unadjusted mortality varied across quartiles (Q1 to Q4), 54%, 58%, 56%, and 59%, respectively (p = 0.004). After controlling for other variables in the multivariable analysis, patients with the lowest SES (Q1) had a significantly higher mortality than patients in the quartile with the highest (Q4) SES (odds ratio 1.3, CI 1.1 to 1.5). In conclusion, patients admitted to the hospital with AF have varying mortality based on their SES. After controlling for co-morbidities, patients with AF and lower SES scores had higher mortality. Further research studies are warranted to study this risk of increased mortality in AF population.