Dataset Information

A National County-Level Assessment of U.S. Nursing Facility Characteristics Associated with Long-Term Exposure to Traffic Pollution in Older Adults.

ABSTRACT: Long-term exposure to ambient air pollution increases disease risk in older adults. Nursing facilities located near major roadways potentially expose older adults to traffic pollution. No studies, however, have described the association between nursing facilities and traffic pollution. We obtained data on facility- and census-tract-level characteristics of 15,706 U.S. facilities from the Medicare Nursing Home Compare datasets. We calculated distance to major roadways and traffic density for each facility. In the contiguous U.S. (as of 2014), 345,792 older adults, about 27% of residents in non-hospital facilities, lived within 150 m major roadways (A1 or A2) in 3876 (28% of sampled) facilities. Nationally, for-profit facilities, high-occupancy facilities, and facilities in census tracts with higher percentages of minorities were more likely to have higher exposure to traffic. Counties in Virginia, New York City, and Rhode Island have the highest percent of residents and facilities near major roads. Nationally, over one-quarter of sampled facilities are located near major roadways. Attributes potentially associated with higher exposure to traffic included "for-profit" and "higher minority census tract". Proximity to major roadways may be an important factor to consider in siting nursing facilities. Our results inform potential intervention strategy at both county and facility level.

SUBMITTER: Wang Y

PROVIDER: S-EPMC5877032 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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A National County-Level Assessment of U.S. Nursing Facility Characteristics Associated with Long-Term Exposure to Traffic Pollution in Older Adults.

Wang Yi Y Fan Hao H Banerjee Rudy R Weaver Anne M AM Weiner Michael M

International journal of environmental research and public health 20180310 3

Long-term exposure to ambient air pollution increases disease risk in older adults. Nursing facilities located near major roadways potentially expose older adults to traffic pollution. No studies, however, have described the association between nursing facilities and traffic pollution. We obtained data on facility- and census-tract-level characteristics of 15,706 U.S. facilities from the Medicare Nursing Home Compare datasets. We calculated distance to major roadways and traffic density for each ...[more]

PMID: 29534437

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Project description:The spread of Coronavirus Disease 2019 (COVID-19) across the United States confirms that not all Americans are equally at risk of infection, severe disease, or mortality. A range of intersecting biological, demographic, and socioeconomic factors are likely to determine an individual's susceptibility to COVID-19. These factors vary significantly across counties in the United States, and often reflect the structural inequities in our society. Recognizing this vast inter-county variation in risks will be critical to mounting an adequate response strategy. Using publicly available county-specific data we identified key biological, demographic, and socioeconomic factors influencing susceptibility to COVID-19, guided by international experiences and consideration of epidemiological parameters of importance. We created bivariate county-level maps to summarize examples of key relationships across these categories, grouping age and poverty; comorbidities and lack of health insurance; proximity, density and bed capacity; and race and ethnicity, and premature death. We have also made available an interactive online tool that allows public health officials to query risk factors most relevant to their local context. Our data demonstrate significant inter-county variation in key epidemiological risk factors, with a clustering of counties in certain states, which will result in an increased demand on their public health system. While the East and West coast cities are particularly vulnerable owing to their densities (and travel routes), a large number of counties in the Southeastern states have a high proportion of at-risk populations, with high levels of poverty, comorbidities, and premature death at baseline, and low levels of health insurance coverage. The list of variables we have examined is by no means comprehensive, and several of them are interrelated and magnify underlying vulnerabilities. The online tool allows readers to explore additional combinations of risk factors, set categorical thresholds for each covariate, and filter counties above different population thresholds. COVID-19 responses and decision making in the United States remain decentralized. Both the federal and state governments will benefit from recognizing high intra-state, inter-county variation in population risks and response capacity. Many of the factors that are likely to exacerbate the burden of COVID-19 and the demand on healthcare systems are the compounded result of long-standing structural inequalities in US society. Strategies to protect those in the most vulnerable counties will require urgent measures to better support communities' attempts at social distancing and to accelerate cooperation across jurisdictions to supply personnel and equipment to counties that will experience high demand.

Project description:Higher numbers of registered nurses (RNs) per patient have been associated with improved patient outcomes in acute-care facilities. Variation in and associations of patient care staffing levels and hemodialysis facility characteristics have not been examined previously.Cross-sectional study using Poisson regression to examine associations between patient care staffing levels and hemodialysis facility characteristics.4,800 US hemodialysis facilities in the 2009 Centers for Medicare & Medicaid (CMS) End-Stage Renal Disease Annual Facility Survey (CMS-2744 form).Facility characteristics, including profit status, freestanding status, chain affiliation, and geographic region, adjusted for facility size, capacity, functional type, and urbanicity.Patient care staffing levels, including ratios of RNs, licensed practical nurses (LPNs), patient care technicians (PCTs), composite staff (RN + LPN + PCT), social workers, and dietitians to in-center hemodialysis patients.After adjusting for background facility characteristics, ratios of RNs and LPNs to patients were 35% (P < 0.001) and 42% (P < 0.001) lower, respectively, but the PCT to patient ratio was 16% (P < 0.001) higher in for-profit than nonprofit facilities (rate ratios of 0.65 [95% CI, 0.63-0.68], 0.58 [95% CI, 0.51-0.65], and 1.16 [95% CI, 1.12-1.19], respectively). Regionally, compared to the Northeast, the adjusted RN to patient ratio was 14% (P < 0.001) lower in the Midwest, 25% (P < 0.001) lower in the South, and 18% (P < 0.001) lower in the West. Even after additional adjustments, the large for-profit chains had significantly lower RN and LPN to patient ratios than the largest nonprofit chain, but a significantly higher PCT to patient ratio. Overall composite staffing levels also were lower in for-profit and chain-affiliated facilities. The patterns hold when hospital-based units were excluded.Nursing hours were not available. Two part-time staff were counted as one full-time equivalent, which may not always be accurate.The significant variation in patient care staffing levels and its associations with facility characteristics warrants inclusion in future large-scale hemodialysis outcomes studies. End-stage renal disease networks and hemodialysis facilities should attend to quality assurance and performance improvement initiatives that maximize licensed nurse staffing levels in hemodialysis facilities.

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Project description:Undetected infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) contributes to transmission in nursing homes, settings where large outbreaks with high resident mortality have occurred (1,2). Facility-wide testing of residents and health care personnel (HCP) can identify asymptomatic and presymptomatic infections and facilitate infection prevention and control interventions (3-5). Seven state or local health departments conducted initial facility-wide testing of residents and staff members in 288 nursing homes during March 24-June 14, 2020. Two of the seven health departments conducted testing in 195 nursing homes as part of facility-wide testing all nursing homes in their state, which were in low-incidence areas (i.e., the median preceding 14-day cumulative incidence in the surrounding county for each jurisdiction was 19 and 38 cases per 100,000 persons); 125 of the 195 nursing homes had not reported any COVID-19 cases before the testing. Ninety-five of 22,977 (0.4%) persons tested in 29 (23%) of these 125 facilities had positive SARS-CoV-2 test results. The other five health departments targeted facility-wide testing to 93 nursing homes, where 13,443 persons were tested, and 1,619 (12%) had positive SARS-CoV-2 test results. In regression analyses among 88 of these nursing homes with a documented case before facility-wide testing occurred, each additional day between identification of the first case and completion of facility-wide testing was associated with identification of 1.3 additional cases. Among 62 facilities that could differentiate results by resident and HCP status, an estimated 1.3 HCP cases were identified for every three resident cases. Performing facility-wide testing immediately after identification of a case commonly identifies additional unrecognized cases and, therefore, might maximize the benefits of infection prevention and control interventions. In contrast, facility-wide testing in low-incidence areas without a case has a lower proportion of test positivity; strategies are needed to further optimize testing in these settings.

Dataset Information

A National County-Level Assessment of U.S. Nursing Facility Characteristics Associated with Long-Term Exposure to Traffic Pollution in Older Adults.

Publications

A National County-Level Assessment of U.S. Nursing Facility Characteristics Associated with Long-Term Exposure to Traffic Pollution in Older Adults.

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