Objectives

We examined the association between the size and growth of Latino populations and hospitals' uncompensated care in California.

Methods

Our sample consisted of general acute care hospitals in California operating during 2000 and 2010 (n = 251). We merged California hospital data with US Census data for each hospital service area. We used spatial analysis, multivariate regression, and fixed-effect models.

Results

We found a significant association between the growth of California's Latino population and hospitals' uncompensated care in the unadjusted regression. This association was still significant after we controlled for hospital and community population characteristics. After we added market characteristics into the final model, this relationship became nonsignificant.

Conclusions

Our findings suggest that systematic support is needed in areas with rapid Latino population growth to control hospitals' uncompensated care, especially if Latinos are excluded from or do not respond to the insurance options made available through the Affordable Care Act. Improving availability of resources for hospitals and providers in areas with high Latino population growth could help alleviate financial pressures.

Aims

Insulin resistance (IR) adversely impacts memory and executive functioning in non-Hispanic whites without diabetes. Less is known in Hispanics/Latinos, despite the fact that Hispanics/Latinos have higher rates of insulin resistance than non-Hispanic whites. We investigated the association between IR and cognition and its variation by age.

Methods

Data from 5987 participants 45-74 years old without diabetes from the Hispanic Community Health Study/Study of Latinos. IR was considered continuously using homeostasis model assessment for insulin resistance (HOMA-IR) and also dichotomized based on clinically relevant thresholds for hyperinsulinemia (fasting insulin > 84.73 pmol/L or HOMA-IR > 2.6) and sample-based norms (75th percentile of fasting insulin or HOMA-IR). Cognitive testing included the Brief Spanish English Verbal Learning Test (B-SEVLT), Verbal Fluency, and Digit Symbol Substitution.

Results

There was 90% overlap in participant categorization comparing clinically relevant and sample-based thresholds. In separate fully-adjusted linear regression models, age modified the association between HOMA-IR and Digit Symbol Substitution (p = 0.02); advancing age combined with higher HOMA-IR levels resulted in higher scores. Age also modified the association between clinically relevant hyperinsulinemia and B-SEVLT recall (p = 0.03); with increasing age came worse performance for individuals with hyperinsulinemia.

Conclusion

The relationship of IR with cognition in Hispanics/Latinos without diabetes may reflect an age- and test-dependent state.

Asthma is a heterogeneous disease, with multiple underlying inflammatory pathways and structural airway abnormalities that impact disease persistence and severity. Recent progress has been made in developing targeted asthma therapeutics, especially for subjects with eosinophilic asthma. However, there is an unmet need for new approaches to treat patients with severe and exacerbation-prone asthma, who contribute disproportionately to disease burden. Extensive deep phenotyping has revealed the heterogeneous nature of severe asthma and identified distinct disease subtypes. A current challenge in the field is to translate new and emerging knowledge about different pathobiologic mechanisms in asthma into patient-specific therapies, with the ultimate goal of modifying the natural history of disease. Here, we describe the Precision Interventions for Severe and/or Exacerbation-Prone Asthma (PrecISE) Network, a groundbreaking collaborative effort of asthma researchers and biostatisticians from around the United States. The PrecISE Network was designed to conduct phase II/proof-of-concept clinical trials of precision interventions in the population with severe asthma, and is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health. Using an innovative adaptive platform trial design, the PrecISE Network will evaluate up to 6 interventions simultaneously in biomarker-defined subgroups of subjects. We review the development and organizational structure of the PrecISE Network, and choice of interventions being studied. We hope that the PrecISE Network will enhance our understanding of asthma subtypes and accelerate the development of therapeutics for severe asthma.