Results for “rural communities” — Page 11

DOE OSTI2023

How long were older people expected to live with or without sarcopenia? Multistate modeling of a national cohort study

Objectives Sarcopenia is well known to be associated with mortality, but there is a lack of evidence on the estimates of life expectancy (LE) for sarcopenia in China. This study aims to estimate total life expectancy (TLE) and sarcopenia-specific LE in community-dwelling older Chinese adults with and without sarcopenia. Methods This study included participants aged 60 years and older who enrolled in the cohort in 2011 and 2013 and at least completed one follow-up until 2015 as part of the China Health and Retirement Longitudinal Study (CHARLS). The criteria for defining sarcopenia were based on the guidelines established by the Asian Working Group on Sarcopenia in 2019. TLE and sarcopenia-specific LE were estimated for the total population and subgroups using continuous-time multistate modeling. Results A total of 6,029 participants (49.2% women) with an average age of 68.4 (SD: 6.56) years were included in the study. The baseline prevalence of sarcopenia and possible sarcopenia was 19.5 and 44.9%, respectively. We observed that sarcopenia stages naturally deteriorated to worse stages (including death, by 24.4%) and returned to better stages (17.1%) during a median follow-up of 3.92 years (IQR: 2.00 ~ 4.00). The average TLE at the age of 60 was 20.9 [95% CI: 20.2–21.5] years (22.1 [95% CI: 19.6–24.6] for non-sarcopenic older adults, 20.9 [95% CI: 19.5–22.3] for possible sarcopenic, and 18.7 [95% CI: 16.4–21.1] for sarcopenic). Men, former and current smokers, and those living in northwest China had less TLE. Sarcopenic older adults, those with lower education, those who are unmarried, those with agriculture hukou, and those living in rural and northwest China were expected to live fewer years with non-sarcopenia. Sarcopenic older people, men, those with agriculture hukou, and those living in rural and southwest China were expected to live more years with sarcopenia. Discussion The results improved our understanding of the relationship between sarcopenia and life expectancy. We suggested that targeted strategies should be considered in high-risk populations and underdeveloped regions to prevent sarcopenia and improve non-sarcopenic life years for the older population.

Ye, Bo↗

DOE OSTI2025

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗