The CalEnviroScreen created by the Office of Environmental Health Hazard Assessment, Sacramento, USA, is a place-based dataset developed to measure environmental and social indicators that are theorized to have cumulative health impacts on populations. The objective of this study was to examine the extent to which the composite scores of the CalEnviroScreen tool are associated with pediatric asthma hospitalization. This was a retrospective analysis of California hospital discharge data from 2010 to 2012. Children who were hospitalized for asthma-related conditions, were aged 0–14 years, and resided in California were included in analysis. Rates of hospitalization for asthma-related conditions among children residing in California were calculated. Poisson multilevel modeling was used to account for individual- and neighborhood-level risk factors. Every unit increase in the CalEnviroScreen Score was associated with an increase of 1.6% above the mean rate of pediatric asthma hospitalizations (rate ratio (RR) = 1.016, 95% confidence interval (CI) = 1.014–1.018). Every unit increase in racial/ethnic segregation and diesel particulate matter was associated with an increase of 1.1% and 0.2% above the mean rate of pediatric asthma, respectively (RR = 1.011, 95% CI = 1.010–1.013; RR = 1.002, 95% CI = 1.001–1.004). The CalEnviroScreen is a unique tool that combines socioecological factors and environmental indicators to identify vulnerable communities with major health disparities, including pediatric asthma hospital use. Future research should identify mediating factors that contribute to community-level health disparities.

At least 15–20% of the population in the world suffers from urticaria. Allergy triggers contribute to the development of urticaria. Not much is known about the demographic and environmental risk factors that contribute to the occurrence of acute urticaria. Methods: We utilized emergency department data on acute urticaria-related visits managed by the California Office of Statewide Planning and Operations for 201 zip codes located in southern central California (San Joaquin Valley) collected during the years 2016 and 2017. Census data from the same zip codes were considered as a population at risk. Socioeconomic and environmental parameters using CalEnviroScreen (Office of Environmental Health Hazard Assessment, Sacramento, CA, USA) database for the zip codes were evaluated as risk factors. Results: The incidence rate of acute urticaria in San Joaquin Valley during 2016–2017 was 1.56/1000 persons (n = 14,417 cases). Multivariate Poisson analysis revealed that zip codes with high population density (RR = 2.81), high percentage of farm workers (RR = 1.49), and the composite of those with high and medium percentage of poverty and those with high and medium percentage of non-white residents (RR = 1.59) increased the likelihood of the occurrence of acute urticaria. Conclusion: High population density, farm work, poverty and minority status is associated with a high risk of having acute urticaria.

In Bangladesh, the number of privately owned hospitals has increased manifold over the last three decades, indicating high profitability in this sector. This study identifies the factors that affect the profit-generating ability of these hospitals. Using 185 privately owned ‘for-profit’ hospitals, the study applied Data Envelopment Analysis (DEA) technique to measure their profit efficiency and then used tobit regression analysis to identify the factors affecting profit efficiency. It was found that only a handful of private hospitals were profit-efficient. Results provide evidence that hospitals located in major metropolitan cities were more efficient than those located in semi-rural areas. It was also found that hospitals that had been in business longer and those that had less market share were likely to be more profit-efficient.

Introduction: Providing health insurance to the poor has become a standard policy response to health disparities between the poor and the non-poor. It is often assumed that if the poor people are given health insurance, they will use preventative care, which will prevent more expensive emergency visits and inpatient hospitalization, and in turn, it will save healthcare cost in the long run. This paper presents the findings from our study in California about what happens to the poor when they are given health insurance. The purpose of the study was to understand how the healthcare system in California treats the poor patients differently than the non-poor. Method: Using multivariate logistic regressions, this study analyzed a large patient discharge data (PDD) from the California Office of Statewide Planning and Development (OSHPD) for eight counties in the Central Valley California (N = 423,640). First, utilizing International Classification of Diseases (ICD 10) as diagnostic criteria, mental-health vs. non-mental health hospitalization rates were estimated. Second, health insurance status was used as a proxy measure of poverty of the patients. Using chi-Square, the probability of hospitalization for mental health services was estimated based on their insurance types. Finally, using step-wise logistic regression, the odds of mental health hospitalization was estimated conditional on individual characteristics, health insurance types, and geographic characteristics. Findings: When the poor people were given health insurance, they were three times more likely to be hospitalized for mental health services than the non-poor. The more than three-fold variation in mental health hospitalization was not driven by demographic or geographic characteristics. The findings are new and have important implications for the healthcare policies for the poor. Further studies are needed to understand the extent to which the disproportionately high rate of mental health hospitalizations of the poor are driven by the provider-induced needs.