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Background Atmospheric particulate matter (PM) has been associated with endothelial dysfunction, an early marker of cardiovascular risk. Our aim was to extend this research to a genetically homogenous, geographically stable rural population using location-specific moving-average air pollution exposure estimates indexed to the date of endothelial function measurement. Methods We measured endothelial function using brachial artery flow-mediated dilation (FMD) in 615 community-dwelling healthy Amish participants. Exposures to PM < 2.5 μm (PM 2.5 ) and PM < 10 μm (PM 10 ) were estimated at participants’ residential addresses using previously developed geographic information system-based spatio-temporal models and normalized. Associations between PM exposures and FMD were evaluated using linear mixed-effects regression models, and polynomial distributed lag (PDL) models followed by Bayesian model averaging (BMA) were used to assess response to delayed effects occurring across multiple months. Results Exposure to PM 10  was consistently inversely associated with FMD, with the strongest (most negative) association for a 12-month moving average (− 0.09; 95% CI: − 0.15, − 0.03). Associations with PM 2.5  were also strongest for a 12-month moving average but were weaker than for PM 10  (− 0.07; 95% CI: − 0.13, − 0.09). Associations of PM 2.5  and PM 10  with FMD were somewhat stronger in men than in women, particularly for PM 10 . Conclusions Using location-specific moving-average air pollution exposure estimates, we have shown that 12-month moving-average estimates of PM 2.5  and PM 10  exposure are associated with impaired endothelial function in a rural population.

A concrete block plant located in Bladensburg, Maryland, wants to expand to include a concrete batching plant on the same property. This expansion could further degrade air quality and impact the health of vulnerable residents. The purpose of this study is to provide information on volatile organic compounds (VOCs) levels near residential areas close to commuter traffic and industrial activity associated with the concrete plant. Air quality monitoring was conducted in the community at five sites: (1) Kingdom Missionary Baptist Church, (2) Bladensburg Waterfront Park, (3) Confluence area, (4) Bladensburg Elementary School, and (5) Hillcrest Apartment Complex by using the Atmotube, a wearable, real-time sensor that can measure total VOCs. Sampling was conducted in 30-minute periods to capture morning onpeak, afternoon off-peak, and evening on-peak periods. Traffic counts were also conducted at the sites mentioned earlier to evaluate vehicular activity. Average 30-minute values for cars ranged from 8.33 to 1295.33 cars, whereas mean truck values ranged from 0.00 to 137.67 trucks across all sites. The highest average car count of 1295.33 cars was observed at the confluence area. Mean VOCs concentrations ranged from 0.11 to 0.54 ppm across the monitoring locations. The maximum average VOCs level of 0.54 ppm was observed at Kingdom Missionary Baptist Church on Saturday. Also, the mean VOCs levels observed at the church (0.54 and 0.31 ppm) were higher compared with other locations on Saturday. Our results revealed spatial variations of VOCs levels across all locations. There were higher total VOCs levels at the church, which is the closest location to the concrete block plant.

Lack of access to a health-promoting food environment can lead to poor health outcomes including obesity which is a problem for African-Americans in Prince George’s County, Maryland. Previous research examined the quality of the food environment at the regional level but did not consider local level indicators. In this study, we utilized an environmental justice framework to examine the local food environment in the County. We collected data from 127 food outlets, (convenience stores, grocery stores, and supermarkets), in three racially and socioeconomically diverse communities – Bladensburg (predominantly African American/ Black, with the lowest median household income); Greenbelt (similar percentage of non-white persons as Hyattsville, with the highest median household income); and Hyattsville (dominated by a Hispanic population). We examined the availability, quality, and accessibility of food within each community, using a modified version of the Johns Hopkins Center for a Livable Future (CLF) healthy food availability index (HFAI).We also used ArcMap 10.6 to examine the spatial distribution of stores in relation to sociodemographic factors and generate descriptive statistics to examine HFAI score differences across the communities, sociodemographic composition, and store types at the block group level. Mean HFAI scores were 7.76, 10.75, and 9.60 for Bladensburg, Greenbelt, and Hyattsville, respectively suggesting a relative disparity in access to diverse healthy and good quality food sources for these communities although these differences were not statistically significant (p=0.79). Statistically significant differences between the communities were found with respect to ethnic stores, stores that sold fresh vegetables (p=0.047), and stores that sold fresh fruits (p=0.012). Getis-Ord Gi Hot Spot Analysis revealed one statistically significant cold spot at 95% confidence, and two others at 90% confidence in Hyattsville, indicating a cluster of low-scoring stores. The results indicate a potential need for expanded food infrastructure in these communities to improve public health. We also identified the need for culturally appropriate foods and proposed ethnic stores as potential salutogens to improve the food environment in culturally diverse neighborhoods.

Having first reached epidemic proportions in coastal metropolitan areas, COVID-19 has spread 4 around the country. Reported case rates vary across counties from zero to 125 per thousand 5 population (around a state prison in the rural county of Trousdale, Tennessee). Overall, rural 6 counties are underrepresented relative to their share of the population, but a growing proportion 7 of all daily cases and deaths have been reported in rural counties. This analysis uses daily 8 reports for all counties to present the trends and distribution of COVID-19 cases and deaths in 9 rural counties, from late March to May 16, 2020. I describe the relationship between population 10 density and case rates in rural and non-rural counties. Then I focus on noteworthy outbreaks 11 linked to prisons, meat and poultry plants, and nursing homes, many of which are linked to 12 high concentrations of Hispanic, American Indian, and Black populations. The growing 13 epidemic in rural counties is apparently driven by outbreaks concentrated in these institutional 14 settings, which are conducive to transmission. The impact of the epidemic in rural areas may 15 be heightened due to their weaker health infrastructure and more vulnerable populations, 16 especially due to age, socioeconomic status, and health conditions. As a result, the epidemic 17 may contribute to the ongoing decline of health, economic, and social conditions in rural areas.

BACKGROUND: Past research shows that among individuals with substance use disorders, the presence of a co-occurring mental illness can influence the initiation, course, and success of behavioral health treatment, but little research has examined people with opioid use disorder (OUD) specifically. METHODS: Using the 2008-2014 National Survey on Drug Use and Health, this study examines the utilization of substance use disorder and mental health treatment among individuals with OUD and different degrees of mental illness severity. The study also examined types of treatment, perceived unmet need for treatment, and barriers to care. RESULTS: 47% of individuals with OUD and co-occurring mild/moderate mental illness did not receive any behavioral health treatment, and 21% of those with co-occurring serious mental illnesses did not receive any behavioral health treatment. Among those with OUD and co-occurring mild/moderate mental illness, 16% reported receiving both substance use disorder and mental health treatment; among those with co-occurring serious mental illness the rate was 32%. The most common form of treatment was prescription medication for mental health, and this was true regardless of whether or not the individual had any mental illness. More than 50% of the study population reported financial difficulties as a barrier to treatment. CONCLUSION: A high proportion of individuals with OUD and co-occurring mental illness are not receiving needed care. However, nearly one in five of those with OUD but no diagnosed mental illness is receiving prescription medication for mental illness. These findings suggest that there is a need to better facilitate access to and coordinate behavioral health care across settings for individuals with OUD. Published by Elsevier Inc.

ABSTRACT: The Affordable Care Act (ACA) provides financial incentives to prevent substance use disorders (SUDs). Local health departments (LHDs) can receive funds to establish care teams that partner with primary care providers and health systems. This study estimates the potential effect of LHDs on emergency visits for SUDs, using linked data sets from the Healthcare Cost and Utilization Project Emergency Department (ED) sample for the State of Maryland-2012, the National Association of County and City Health Officials Profiles Survey 2013, and Area Health Resource File 2013 to estimate potential effect of LHDs' provision of SUD preventive care and SUD-related policy implementation. Local health department involvement in SUD-related policy during the past 2 years and provision of preventive care for behavioral health in the past year significantly reduced the probability of having a SUD-related ED visit by 11% and 6%, respectively, after controlling for individual characteristics (odds ratio [OR] = 0.89, p < .001; OR = 0.93, p < .001). After adjusting for the individual and contextual factors, LHD involvement in policy was still associated with 14% reduction in SUD-related ED visits (OR = 0.86, p < .001). Results offer insights on the extent to which the LHD activities can possibly affect SUD-related ED visits and provide a foundation for future work to identify effective LHD interventions. 

Importance: Nearly 34 million adults – 17 percent of all American adults – have co-occurring mental and physical health conditions. However, the extent to which increased health insurance coverage has facilitated access to needed health care services among this population remains unclear. Objective: Prior research suggests that people with serious psychological distress (SPD) and cancer, heart disease, diabetes, asthma, or hypertension report worse access to care than people with the same physical conditions but no SPD. While the recent expansion in health insurance coverage was expected to improve access to care for people with SPD, access barriers that people with SPD report remain underexplored. Setting: Using the cross-sectional data from the National Health Interview Survey 2011-2015, we examined self-reported health care access barriers among adults (between ages 18 to 64) with SPD and co-occurring physical health conditions. Results: Our sample included 45,294 individuals with chronic conditions (heart disease, high blood pressure, diabetes, cancer, or asthma). Among them, 3,639 also had SPD. After controlling for demographic and socioeconomic factors, results of multivariate logistic regressions showed that individuals with co-occurring SPD and a physical health condition were significantly more likely to report that they had worse health insurance coverage compared to the prior year (OR=1.32, p<0.01), that doctor's office informed that they were not accepting new patients (OR=2.09, p<0.001), that the doctor's office stated they did not accept the particular health insurance they have (OR=1.98, p<0.001), that they couldn't get an appointment soon enough (OR=2.42, p<0.001), they had no transportation to get to the doctor (OR=3.23, p<0.001), and that overall they had trouble finding a doctor/provider (OR=2.12, p<0.001). Conclusions: Our results suggest that despite an increase in health insurance coverage between 2011 and 2015, barriers to access remain a significant concern for individuals with co-occurring SPD and physical health conditions.

Objectives:  We examined changes in  health care access  and utilization associated with the Patient Protection and  Affordable Care Act  (ACA) for different Asian American subgroups relative to non-Latino whites (whites). Research Design:  Using 2003–2017 California Health Interview Survey data, we examined changes in 4  health care access  measures and 2 utilization measures among whites and 7 Asian American subgroups. We estimated the unadjusted and adjusted percentage point changes on the absolute scale from the pre-ACA to post-ACA periods. Adjusted estimates were obtained from multivariable logistic regression models that controlled for predisposing, enabling, and need factors. We also estimated the pre-ACA to post-ACA changes between whites and Asian American subgroups using a difference-in-difference approach. Results:  After the ACA was implemented, uninsurance decreased among all Asian American subgroups, but improvements in disparities relative to whites in these measures were limited. In particular, Koreans had the largest absolute reduction in uninsurance (−16.8 percentage points) and were the only subgroup with a significant reduction in terms of disparities relative to whites (−10.1 percentage points). However, little or no improvement was observed in the other 3 access measures (having a usual source of care, delayed medical care in past year, or delayed prescription drug use in past year) and 2 utilization measures (having a physician visit or emergency department visit in past year). Conclusions:  Despite coverage gains among Asian American subgroups, especially Koreans, disparities in access and utilization persisted across all Asian American subgroups.

Utilization of cost-effective essential preventive health services increased after the implementation of the Affordable Care Act’s (ACA) provision that non-grandfathered private insurers provide cost-effective preventive services without cost sharing in 2010. Little is known, however, whether this change is also observed among Asians in the US. We examined patterns of preventive services utilization among Asian subgroups relative to non-Latino whites (whites) after the implementation of the ACA’s preventive services provisions. Using 2013–2016 Medical Expenditure Panel Survey data, we examined utilization trends in preventive services among Asian Indians, Chinese, Filipinos, and other Asians relative to whites. We also ran logistic regression models to estimate the likelihood of having received each of the seven essential preventive services (routine checkups, flu vaccinations, cholesterol screenings, blood pressure checkups, Papanicolaou “pap” tests, mammograms, and colorectal cancer screenings). Compared to whites, Asians had higher rates of utilization of routine checkups, cholesterol screenings, and flu vaccinations, but they had lower utilization rates of blood pressure checkups, pap tests, and mammograms. The patterns of preventive services utilization differed across the Asian subgroups. All Asian subgroups, except for Filipinos, were less likely to have pap tests or mammograms than whites. Moreover, we observed a decreasing trend in having pap tests, mammograms, or colorectal cancer screenings among all Asian subgroups between 2013 and 2016. Our findings suggest that there are low cancer screening rates across Asian subgroups. This indicates the need for programs tailored to specific Asian subgroups to improve cancer screening.

Objective: We examined changes in insurance coverage and health care utilization associated with the Affordable Care Act (ACA) among subgroups of Asian youth relative to non-Latino white youth. Methods: Data were from the 2010-2017 American Community Survey and National Health Interview Survey. Difference-in-difference models were used to examine changes in insurance coverage and health care utilization associated with the ACA among subgroups of Asian youth relative to white youth and subgroups of Asian youth in households below 200% of the federal poverty level (FPL) relative to comparable white youth. Results: Since the implementation of the ACA, insurance coverage increased among all Asian subgroups and white youth. The magnitude of the increase in insurance coverage was larger among Asian subgroups than white youth. More pronounced increases were found among almost all Asian subgroups in households below 200% FPL. Changes in health care utilization were limited and varied by subgroup. Increases in well-child visits were observed only among Chinese and “other” Asian youth. Conclusions: Insurance coverage increased among Asian youth after the implementation of the ACA. Improvements in health care utilization were limited and differed by subgroups. Programs to improve health care utilization should be tailored to Asian youth according to subgroup.