Clinicas de Salud del Pueblo

BackgroundValid, reliable measures of psychosocial constructs are needed in oral health research. This study quantitatively evaluated the psychometric properties of nine new Oral Health Behavior Social Support (OHBSS) scales, which measured support for three oral health behaviors (brushing, flossing, dental care), queried for each of three sources (family, health providers, others/friends).MethodsYoung Mexican-origin adults in the southwestern United States-Mexico border region completed an online survey, in English or Spanish (N = 502). Survey items included: OHBSS scales, general social support scales, oral health behaviors, self-rated oral health status, dental anxiety, acculturation and socio-demographics. Subsample 1 participants also completed a dental exam (N = 41). Subsample 2 participants also completed a repeat OHBSS survey two-to-six weeks later (N = 56).Psychometric properties were tabulated, overall and by language preference (English or Spanish). Convergent and divergent validity were evaluated via correlations between the dental-specific OHBSS social support scales, scores from three validated general social support scales, and scales expected to be largely unrelated (acculturation, dental anxiety). Correlations examined predictive validity between the OHBSS scales and oral health behaviors, and self-reported and clinical outcomes. Test–retest reliability was assessed via intraclass correlation coefficients in Subsample 2.ResultsOf 502 participants, 60% preferred speaking English, 37% were single, and 21% were male. OHBSS scores indicated that health providers then family provided the most support for all three oral health behaviors, while others/friends did not provide much support. Spanish speakers tended to have higher OHBSS scores than English speakers.Correlations followed expected patterns and supported convergent and divergent validity, in the full sample and across languages. OHBSS scales exhibited many significant weak-moderate positive correlations (r = 0.10–0.38) with general social support scales. Few (11/108) significant correlations (< -0.16) were observed between OHBSS scales, acculturation, and dental anxiety. OHBSS scales exhibited some significant weak-moderate positive correlations with oral health-promoting behaviors. OHBSS scales were not associated with clinical outcomes. OHBSS scales exhibited good test–retest reliability overall and in Spanish.ConclusionPsychometric properties for the OHBSS scales were acceptable in both English and Spanish versions. The scales are valid and reliable tools for assessing social support for oral health-promoting behaviors from family, health providers, and others/friends.Trial registrationNot applicable.

The discussion of antimicrobial resistance has begun to impact consumer preference and influence the implementation of certain growth-promoting technologies in the cattle feeding industry [...].

ABSTRACT This is a case study of a 55-year-old woman presenting with dystrophic nails that arose during her teenage years and has worsened over the last few years. The patient reported frequent wet work, exposure to irritants, and cuticle manipulation. The physical examination showed proximal nail fold bolstering, loss of cuticle, and a wavy dorsal nail plate resembling a “washboard.” She was diagnosed with chronic paronychia and onychotillomania. She was prescribed clobetasol ointment and sulfacetamide in ethanol and was counseled on hygiene and at-home care. One month after the regimen was started, there was noticeable reduction of inflammation to the cuticle.

Additive manufacturing (AM) enables the production of parts with extremely complex shapes, such as lattice structures and internal structures (cavities, channels). As a result of this geometric complexity, the applicability of most conventional nondestructive testing (NDT) techniques to AM parts is limited, and innovative volumetric NDT methods are needed for quality control. Few established volumetric NDT methods are suitable for inspecting the integrity of parts with complex geometries. X-ray computed tomography (XCT) is widely recognized as the most powerful method for detecting and evaluating the dimensions of structural flaws and also for checking the compliance of parts with their numerical model. However, it is an expensive method. The image analysis takes more time than is appropriate for routine inspection, and the files are large and, thus, difficult to handle. Furthermore, XCT is not suitable for large and high-density parts. Alternative methods are therefore needed. Investigation of resonant acoustic methods such as resonant ultrasound spectroscopy (RUS) or electromagnetic-acoustic resonance methods, linear or nonlinear, has shown great potential. RUS methods are global, enabling identification of defective parts based on analysis of their natural resonant frequencies. There are several variants of RUS methods, but their basic principles are similar. They can inspect any part shape, and they are insensitive to inherent surface roughness. In addition, although they are global volumetric methods (“pass/fail”), they can inspect parts of any size, unlike XCT, which can determine the locations of defects but is restricted by the size or density of the parts. Moreover, compared to XCT, they are simple to implement, easy to use, quite affordable, and the inspection of the parts is particularly fast, which is very suitable for routine inspection. This article describes the capabilities of various linear RUS methods, as well as a nonlinear electromagnetic-acoustic resonance method for quality assurance of AM parts.

Objetivo: Determinar los factores clínicos y epidemiológicos relacionados a infección de tracto urinario (ITU) en pacientes atendidos en el Centro de Salud Pueblo Nuevo, 2021. Materiales y métodos: Se desarrolló un estudio observacional, retrospectivo de nivel correlacional que revisó 83 historias clínicas de pacientes atendidos en un centro primario de salud. Los datos fueron extraídos con una ficha de recolección validada por expertos siguiendo un análisis documental de los registros médicos. El análisis se llevó a cabo en SPSS versión 25.0 con estadísticas descriptivas e inferenciales. Resultados: La edad media de los pacientes fue de 42,39 ± 16,62 años, donde el 81,93% (n=68) era mujer, 74,70% (n=62) tenía educación secundaria, 60,24% (n=50) tenía sobrepeso, el 22,89% (n=19) era diabético y 20,48% (n=17) padecía de litiasis renal. El análisis bivariado reveló que aquellos pacientes con diabetes mellitus tipo 2 (DM2) (p&lt;0,001), con litiasis renal (p&lt;0,001) y de género femenino (p=0,005) se relacionaron significativamente con la presencia de ITU. Conclusiones: Los pacientes atendidos en el Centro de Salud Pueblo Nuevo presentan una alta frecuencia de ITU, donde la DM2, litiasis renal y género femenino son los factores más importantes relacionados con esta patología.

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Summary:The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772