Initial home dialysis is increased for rural patients by accessing urban facilities

Background: The 240,000 rural patients with end stage kidney disease in the United States have less access to nephrology care and higher mortality than those in urban settings. The Advancing American Kidney Health initiative aims to increase the use of home renal replacement therapy. Little is known about how rural patients access home dialysis and the availability and quality of rural dialysis facilities. Methods: Incident dialysis patients in 2017 and their facilities were identified in the United States Renal Data System. Facility quality and service availability was analyzed with descriptive statistics. We assessed the availability of home dialysis methods depending on rural versus urban counties, and then we used multivariate logistic regression to identify the likelihood of rural patients with home dialysis as their initial modality and the likelihood of rural patients changing to home dialysis within 90 days. Finally, we assessed mortality after dialysis initiation based on patient home location. Results: Of the 97,930 dialysis initiates, 15,310 (15.6%) were rural. Rural dialysis facilities were less likely to offer home dialysis (51.4% vs 54.1%, P<0.001). While a greater proportion of rural patients (9.2 vs 8.2%, P<0.001) were on home dialysis, this was achieved by traveling to urban facilities to obtain home dialysis (OR 2.74, P<0.001). After adjusting for patient and facility factors, rural patients had a higher risk of mortality (HR 1.06, P=0.004). Conclusions: Despite having fewer facilities that offer home dialysis, rural patients were more often on home dialysis methods because they traveled to urban facilities, representing an access gap. Even if rural patients accessed home dialysis at urban facilities, rural patients still suffered worse mortality. Future dialysis policy should address this access gap to improve care and overall mortality for rural patients.

Access to advanced-level hospital care: differences in prehospital times calculated using incident locations compared with patients’ usual residence

Studies estimate that 84% of the USA and New Zealand’s (NZ) resident populations have timely access (within 60 min) to advanced-level hospital care. Our aim was to assess whether usual residence (ie, home address) is a suitable proxy for location of injury incidence. In this observational study, injury fatalities registered in NZ’s Mortality Collection during 2008–2012 were linked to Coronial files. Estimated access times via emergency medical services were calculated using locations of incident and home. Using incident locations, 73% (n=4445/6104) had timely access to care compared with 77% when using home location. Access calculations using patients’ home locations overestimated timely access, especially for those injured in industrial/construction areas (18%; 95% CI 6% to 29%) and from drowning (14%; 95% CI 7% to 22%). When considering timely access to definitive care, using the location of the injury as the origin provides important information for health system planning.

Urinary Organophosphate Metabolites and Metabolic Biomarkers of Conventional and Organic Farmers in Thailand

Organophosphate (OP) pesticides are used by most farmers to remove insects and to increase productivity; however, questions remain on the long-term health impacts of their use. This study assessed the relationship between OP biomarker levels and metabolic biomarker parameters. Conventional farmers (n = 213) and organic farmers (n = 225) were recruited, interviewed, and had physical health examinations. Serum glucose and lipid profiles, triglycerides, total cholesterol, high-density lipoproteins (HDL), and low-density lipoproteins (LDL) were measured. The average age, gender, education, and self-reported agricultural work time, work in second jobs, smoking status, alcohol consumption, insecticide use at home, home location near farmlands and years of pesticide use were significantly different between the conventional and organic farmers. The urinary OP metabolite levels were also significantly different between the two groups. With an increase in urinary diethyl phosphate, dimethyl phosphate and dialkyl phosphate metabolites, the total cholesterol, LDL and HDL, were significantly increased for all farmers after controlling for age, gender, alcohol consumption, years of pesticide use, and home location near farmlands. The results are consistent with our previous studies which suggests that pesticide usage, especially organophosphates, may increase the risk of cardiovascular disease and stroke among Thai farmers.

The evolution of choice set formation in dwelling and location with rising prices: A decadal panel analysis in the Greater Toronto Area

Home location choice is based on both the characteristics of the dwelling (e.g., size, style, number of bedrooms) and the location (e.g., proximity to work, quality of schools, accessibility). Recent years have seen a steep increase in the price of housing in many major cities. In this research, we examine how these price increases are affecting the types of dwelling and locations considered by households. A large sample of real estate listings from 2006 and 2016 from the Greater Toronto Area is used to develop the empirical models. Two recently developed discrete choice models are used in the study: a nested logit model with latent class feedback (LCF) and a semi-compensatory independent availability logit (SCIAL) model. A method of alternative aggregation is proposed to overcome the computational hurdle that often impedes the estimation of choice set models. We find a significant increase in the probability of larger households considering townhouses and apartments over detached single-family dwellings between 2006 and 2016.

A Data-Driven Framework for Analyzing Spatial Distribution of the Elderly Cardholders by Using Smart Card Data

In this era of population aging, it is essential to understand the spatial distribution patterns of the elderly. Based on the smart card data of the elderly, this study aims to detect the home location and examine the spatial distribution patterns of the elderly cardholders in Beijing. A framework is proposed that includes three methods. First, a rule-based approach is proposed to identify the home location of the elderly cardholders based on individual travel pattern. The result has strong correlation with the real elderly population. Second, the clustering method is adopted to group bus stops based on the elderly travel flow. The center points of clusters are utilized to construct a Voronoi diagram. Third, a quasi-gravity model is proposed to reveal the elderly mobility between regions, using the public facilities index. The model measures the elderly travel number between regions, according to public facilities index on the basis of the total number of point of interest (POI) data. Beijing is used as an example to demonstrate the applicability of the proposed methods, and the methods can be widely used for urban planning, design and management regarding the aging population.

Identifying Extreme COVID-19 Mortality Risks in English Small Areas: A Disease Cluster Approach

The COVID-19 pandemic is having a huge impact worldwide and has highlighted the extent of health inequalities between countries but also in small areas within a country. Identifying areas with high mortality is important both of public health mitigation in COVID-19 outbreaks, and of longer term efforts to tackle social inequalities in health. In this paper we consider different statistical models and an extension of a recent method to analyze COVID-19 related mortality in English small areas during the first wave of the epidemic in the first half of 2020. We seek to identify hotspots, and where they are most geographically concentrated, taking account of observed area factors as well as spatial correlation and clustering in regression residuals, while also allowing for spatial discontinuities. Results show an excess of COVID-19 mortality cases in small areas surrounding London and in other small areas in North-East and and North-West of England. Models alleviating spatial confounding show ethnic isolation, air quality and area morbidity covariates having a significant and broadly similar impact on COVID-19 mortality, whereas nursing home location seems to be slightly less important.

The impact of COVID-19 on trips to urban amenities: Examining travel behavior changes in Somerville, MA

While there has been much speculation on how the pandemic has affected work location patterns and home location choices, there is sparse evidence regarding the impacts that COVID-19 has had on amenity visits in American cities, which typically constitute over half of all urban trips. Using aggregate app-based GPS positioning data from smartphone users, this study traces the changes in amenity visits in Somerville, MA from January 2019 to December 2020, describing how visits to particular types of amenities have changed as a result of business closures during the public health emergency. Has the pandemic fundamentally shifted amenity-oriented travel behavior or is consumer behavior returning to pre-pandemic trends? To address this question, we calibrate discrete choice models that are suited to Census block-group level analysis for each of the 24 months in a two-year period, and use them to analyze how visitors’ behavioral responses to various attributes of amenity clusters have shifted during different phases of the pandemic. Our findings suggest that in the first few months of the pandemic, amenity-visiting preferences significantly diverged from expected patterns. Even though overall trip volumes remained far below normal levels throughout the remainder of the year, preferences towards specific cluster attributes mostly returned to expected levels by September 2020. We also construct two scenarios to explore the implications of another shutdown and a full reopening, based on November 2020 consumer behavior. While government restrictions have played an important role in reducing visits to amenity clusters, our results imply that cautionary consumer behavior has played an important role as well, suggesting a likely long and slow path to economic recovery. By drawing on mobile phone location data and behavioral modeling, this paper offers timely insights to help decision-makers understand how this unprecedented health emergency is affecting amenity-related trips and where the greatest needs for intervention and support may exist.