919 research outputs found

    Finite Element Analysis of Custom Shoulder Implants Provides Accurate Prediction of Initial Stability

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    Custom reverse shoulder implants represent a valuable solution for patients with large bone defects. Since each implant has unique patient-specific features, finite element (FE) analysis has the potential to guide the design process by virtually comparing the stability of multiple configurations without the need of a mechanical test. The aim of this study was to develop an automated virtual bench test to evaluate the initial stability of custom shoulder implants during the design phase, by simulating a fixation experiment as defined by ASTM F2028-14. Three-dimensional (3D) FE models were generated to simulate the stability test and the predictions were compared to experimental measurements. Good agreement was found between the baseplate displacement measured experimentally and determined from the FE analysis (Spearman’s rank test, p < 0.05, correlation coefficient ΒΏs = 0.81). Interface micromotion analysis predicted good initial fixation (micromotion <150 Β΅m, commonly used as bone ingrowth threshold). In conclusion, the finite element model presented in this study was able to replicate the mechanical condition of a standard test for a custom shoulder implants

    Socio-economic inequalities in injury incidence in the Netherlands

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    Background: Interventions to reduce socio-economic inequalities in injury incidence should be tailored to specific priority areas that may be identified by descriptive studies. We aimed to provide an overview of exist

    Residential area characteristics and disabilities among Dutch community-dwelling older adults

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    Background: Living longer independently may be facilitated by an attractive and safe residential area, which stimulates physical activity. We studied the association between area characteristics and disabilities and whether this association is mediated by transport-related physical activity (TPA). Methods: Longitudinal data of 271 Dutch community-dwelling adults aged 65years and older participating in the Elderly And their Neighbourhood (ELANE) study in 2011-2013 were used. Associations between objectively measured aesthetics (range 0-22), functional features (range 0-14), safety (range 0-16), and destinations (range 0-15) within road network buffers surrounding participants' residences, and self-reported disabilities in instrumental activities of daily living (range 0-8; measured twice over a 9months period) were investigated by using longitudinal tobit regression analyses. Furthermore, it was investigated whether self-reported TPA mediated associations between area characteristics and disabilities. Results: A one unit increase in aesthetics within the 400m buffer was associated with 0.86 less disabilities (95% CI -1.47 to -0.25; p<0.05), but other area characteristics were not related to disabilities. An increase in area aesthetics was associated with more TPA, and more minutes of TPA were associated with less disabilities. TPA however, only partly mediated the associated between area aesthetics and disabilities. Conclusions: Improving aesthetic features in the close by area around older persons' residences may help to prevent disability. Β© 2016 The Author(s)

    Self-reported general health, physical distress, mental distress, and activity limitation by US county, 1995-2012

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    Background: Metrics based on self-reports of health status have been proposed for tracking population health and making comparisons among different populations. While these metrics have been used in the US to explore disparities by sex, race/ethnicity, and socioeconomic position, less is known about how self-reported health varies geographically. This study aimed to describe county-level trends in the prevalence of poor self-reported health and to assess the face validity of these estimates. Methods: We applied validated small area estimation methods to Behavioral Risk Factor Surveillance System data to estimate annual county-level prevalence of four measures of poor self-reported health (low general health, frequent physical distress, frequent mental distress, and frequent activity limitation) from 1995 and 2012. We compared these measures of poor self-reported health to other population health indicators, including risk factor prevalence (smoking, physical inactivity, and obesity), chronic condition prevalence (hypertension and diabetes), and life expectancy. Results: We found substantial geographic disparities in poor self-reported health. Counties in parts of South Dakota, eastern Kentucky and western West Virginia, along the Texas-Mexico border, along the southern half of the Mississippi river, and in southern Alabama generally experienced the highest levels of poor self-reported health. At the county level, there was a strong positive correlation among the four measures of poor self-reported health and between the prevalence of poor self-reported health and the prevalence of risk factors and chronic conditions. There was a strong negative correlation between prevalence of poor self-reported health and life expectancy. Nonetheless, counties with similar levels of poor self-reported health experienced life expectancies that varied by several years. Changes over time in life expectancy were only weakly correlated with changes in the prevalence of poor self-reported health. Conclusions: This analysis adds to the growing body of literature documenting large geographic disparities in health outcomes in the United States. Health metrics based on self-reports of health status can and should be used to complement other measures of population health, such as life expectancy, to identify high need areas, efficiently allocate resources, and monitor geographic disparities

    ЭлСктромагнитная обстановка Π² ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½Ρ‹Ρ… классах, Π΅Π΅ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ Π½ΠΎΡ€ΠΌΠ°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ

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    ΠŸΡ€ΠΈΠ²Π΅Π΄Π΅Π½Ρ‹ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ исслСдования элСктромагнитной обстановки (ЭМО), создаваСмой ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π°ΠΌΠΈ Π² ΡƒΡ‡Π΅Π±Π½Ρ‹Ρ… помСщСниях. Показано, Ρ‡Ρ‚ΠΎ Π² зависимости ΠΎΡ‚ мСста располоТСния ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π° ΠΌΠ΅Π½ΡΡŽΡ‚ΡΡ Ρ€Π°Π·ΠΌΠ΅Ρ€Ρ‹, создаваСмой ΠΈΠΌ Π·ΠΎΠ½Ρ‹ опасного излучСния, Π΄Π°Π½Ρ‹ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΈ ΠΏΠΎ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŽ ЭМО ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌ Π΅Π΅ Π½ΠΎΡ€ΠΌΠ°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ
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