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Sudden unexpected infant death is the leading cause of infant mortality with black white infant mortality remaining at 21 for the last decade. Smartphone technology provides a convenient and accessible tool for injury prevention anticipatory guidance among at-risk communities.
A convenience sample of pregnant teen mothers who own a smartphone. During a 1-month postnatal home visit, a safe sleep environment survey was administered, infant sleep practices were observed, and mothers trained to take and submit standard infants' sleep environment photographs. Photographs were independently assessed for inter-rater reliability (IRR) across five sleep safety domains (primary outcome) sleep location, surface, position, presence of soft items, and hazards near the sleep area. Expert and novice coders IRR was measured using Cohen's kappa coefficient (K). Sleep safety correlation between photographs and observation, and parent report and observation was determined.
Sixteen (57.1%) mothers completed the home visit. Most parents reported infants sleeping supine (78.5) in parents' bedroom (85.9%). Photographs demonstrated sleep position, soft items without the baby present, and hanging toys had perfect agreement across all three coder pairs. Safe sleep experts' IRR demonstrated perfect agreement for sleep location, position, and soft items. While 83.8% of parents were observed putting their infants down to sleep on their back, 78.5% of parents reported doing the same and 82.4% of the photographs demonstrated supine infant sleep position.
Using photographs, coders can reliably categorize some key infant sleep safety aspects, and photograph sleep safety is comparable to parent report and direct observation.
Using photographs, coders can reliably categorize some key infant sleep safety aspects, and photograph sleep safety is comparable to parent report and direct observation.
Given the significant health effects, we assessed geospatial patterns of adverse events (AEs), defined as physical or sexual abuse and accidents or poisonings at home, among children in a mixed rural-urban community.
We conducted a population-based cohort study of children (<18 years) living in Olmsted County, Minnesota, to assess geographic patterns of AEs between April 2004 and March 2009 using International Classification of Diseases, Ninth Revision codes. We identified hotspots by calculating the relative difference between observed and expected case densities accounting for population characteristics (; hotspot ≥ 0.33) using kernel density methods. A Bayesian geospatial logistic regression model was used to test for association of subject characteristics (including residential features) with AEs, adjusting for age, sex, and socioeconomic status (SES).
Of the 30,227 eligible children (<18 years), 974 (3.2%) experienced at least one AE. Of the nine total hotspots identified, five were mobile home communities (MHCs). Among non-Hispanic White children (85% of total children), those living in MHCs had higher AE prevalence compared to those outside MHCs, independent of SES (mean posterior odds ratio 1.80; 95% credible interval 1.22-2.54). MHC residency in minority children was not associated with higher prevalence of AEs. Of addresses requiring manual correction, 85.5% belonged to mobile homes.
MHC residence is a significant unrecognized risk factor for AEs among non-Hispanic, White children in a mixed rural-urban community. Given plausible outreach difficulty due to address discrepancies, MHC residents might be a geographically underserved population for clinical care and research.
MHC residence is a significant unrecognized risk factor for AEs among non-Hispanic, White children in a mixed rural-urban community. Given plausible outreach difficulty due to address discrepancies, MHC residents might be a geographically underserved population for clinical care and research.
Arkansans have some of the worst breast cancer mortality to incidence ratios in the United States (5th for Blacks, 4th for Whites, 7th overall). Screening mammography allows for early detection and significant reductions in mortality, yet not all women have access to these life-saving services. Utilization in Arkansas is well below the national average, and the number of FDA-approved screening facilities has decreased by 38% since 2001. Spatial accessibility plays an important role in whether women receive screenings.
We use constrained optimization models within a geographic information system (GIS) to probabilistically allocate women to nearby screening facilities, accounting for facility capacity and patient travel time. We examine accessibility results by rurality derived from rural-urban commuting area (RUCA) codes.
Under most models, screening capacity is insufficient to meet theoretical demand given travel constraints. Approximately 80% of Arkansan women live within 30 minutes of a screening facility, most of which are located in urban and suburban areas. The majority of unallocated demand was in Small towns and Rural areas.
Geographic disparities in screening mammography accessibility exist across Arkansas, but women living in Rural areas have particularly poor spatial access. Mobile mammography clinics can remove patient travel time constraints to help meet rural demand. More broadly, optimization models and GIS can be applied to many studies of healthcare accessibility in rural populations.
Geographic disparities in screening mammography accessibility exist across Arkansas, but women living in Rural areas have particularly poor spatial access. Mobile mammography clinics can remove patient travel time constraints to help meet rural demand. More broadly, optimization models and GIS can be applied to many studies of healthcare accessibility in rural populations.
The NIH Inclusion Across the Lifespan policy has implications for increasing older adult (OA) participation in research. SR-717 chemical structure This study aimed to understand influential factors and facilitators to rural OA research participation.
Thirty-seven rural adults aged ≥66 years participated in focus groups in community centers in four Oregon "non-metro" counties. Transcribed discussions were coded using open-axial coding by an interdisciplinary analytical team.
Ages were 66-96 (mean 82.2) years. Majority were women (64%) and white (86%). Primary, interrelated discussion themes were Motivation and Facilitators, Perceptions of Research, and Barriers to Research Participation. Participants were motivated to engage in research because they believed research had implications for improved longevity and quality of life and potentially benefited future generations. Motivational factors influencing participation included self-benefit and improving others' lives, opportunities to socialize and learn about current research, research transparency (funding, time commitment, and requirements), and financial compensation.