Childhood obesity is a public health concern in the United States. Consequences of childhood obesity include metabolic disease and heart, lung, kidney, and other health-related comorbidities. ...Therefore, the early determination of obesity risk is needed and predicting the trend of a child's body mass index (BMI) at an early age is crucial. Early identification of obesity can lead to early prevention. Multiple methods have been tested and evaluated to assess obesity trends in children. Available growth charts help determine a child's current obesity level but do not predict future obesity risk. The present methods of predicting obesity include regression analysis and machine learning-based classifications and risk factor (threshold)-based categorizations based on specific criteria. All the present techniques, especially current machine learning-based methods, require longitudinal data and information on a large number of variables related to a child's growth (e.g., socioeconomic, family-related factors) in order to predict future obesity-risk. In this paper, we propose three different techniques for three different scenarios to predict childhood obesity based on machine learning approaches and apply them to real data. Our proposed methods predict obesity for children at five years of age using the following three data sets: (1) a single well-child visit, (2) multiple well-child visits under the age of two, and (3) multiple random well-child visits under the age of five. Our models are especially important for situations where only the current patient information is available rather than having multiple data points from regular spaced well-child visits. Our models predict obesity using basic information such as birth BMI, gestational age, BMI measures from well-child visits, and gender. Our models can predict a child's obesity category (normal, overweight, or obese) at five years of age with an accuracy of 89%, 77%, and 89%, for the three application scenarios, respectively. Therefore, our proposed models can assist healthcare professionals by acting as a decision support tool to aid in predicting childhood obesity early in order to reduce obesity-related complications, and in turn, improve healthcare.
Global 12-month psychosis prevalence is estimated at roughly 0.4%, although prevalence of antipsychotic use in the U.S. is estimated at roughly 1.7%. Antipsychotics are frequently prescribed for off ...label uses, but have also been shown to carry risk factors for certain comorbid conditions and with other prescription medications. The study aims to describe the socio-demographic and health characteristics of U.S. adults taking prescription antipsychotic medications, and to better understand the association of antipsychotic medications and comorbid chronic diseases.
The study pools 2013-2018 data from the National Health and Nutrition Examination Survey (NHANES), a nationally representative cross-sectional survey of non-institutionalized U.S. residents (n = 17,691). Survey staff record prescription medications taken within the past 30 days for each respondent, from which typical and atypical antipsychotic medications were identified.
Prevalence of antipsychotic use among U.S. adults was 1.6% (n = 320). Over 90% of individuals taking antipsychotics reported having health insurance and a usual place for care, significantly more than their counterparts not taking antipsychotics. Further, those taking antipsychotics reported higher prevalence of comorbid chronic diseases and took an average of 2.3 prescription medications more than individuals not taking antipsychotics. Individuals taking antipsychotics were more likely to sleep 9 or more hours per night, be a current smoker, and have a body mass index greater than 30 kg/m
.
U.S. adults who take antipsychotic medications report more consistent health care access and higher prevalence of comorbid chronic diseases compared to those not taking antipsychotics. The higher comorbidity prevalence and number of total prescriptions highlight the need for careful assessment and monitoring of existing comorbidities and potential drug-drug interactions among adults taking antipsychotics in the U.S.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A matrix is proposed to characterize mental health diversion programs and standardize the reporting of program context, outputs, outcomes, and community settings. Data collection for program ...reporting is challenging because individual programs report on what is relevant to local conditions and may omit or overlook important contextual or structural factors that are key to programmatic success or failure. This limits generalizability and comparability. Using a standard matrix reporting framework clearly lists the constructs of the program, context, and community systems. Two diversion programs are reported demonstrating the use of the matrix. Although different jurisdictions have a wide spectrum of agencies and resources available to support diversion, and may approach the concept differently, standardizing and streamlining reporting will assist with evaluation of diversion and the creation of sustainable programs.
The exposome consists of factors an individual is exposed to across the life course. The exposome is dynamic, meaning the factors are constantly changing, affecting each other and individuals in ...different ways. Our exposome dataset includes social determinants of health as well as policy, climate, environment, and economic factors that could impact obesity development. The objective was to translate spatial exposure to these factors with the presence of obesity into actionable population-based constructs that could be further explored.
Our dataset was constructed from a combination of public-use datasets and the Center of Disease Control’s Compressed Mortality File. Spatial Statistics using Queens First Order Analysis was performed to identify hot- and cold-spots of obesity prevalence; followed by Graph Analysis, Relational Analysis, and Exploratory Factor Analysis to model the multifactorial spatial connections.
Areas of high and low presence of obesity had different factors associated with obesity. Factors associated with obesity in areas of high obesity propensity were: poverty / unemployment; workload, comorbid conditions (diabetes, CVD) and physical activity. Conversely, factors associated in areas where obesity was rare were: smoking, lower education, poorer mental health, lower elevations, and heat.
The spatial methods described within the paper are scalable to large numbers of variables without issues of multiple comparisons lowering resolution. These types of spatial structural methods provide insights into novel variable associations or factor interactions that can then be studied further at the population or policy levels.
Most major diseases have important social determinants. In this context, classification of disease based on etiologic or anatomic criteria may be neither mutually exclusive nor optimal.
Units of ...analysis comprised large metropolitan central and fringe metropolitan counties with reliable mortality rates--(n = 416). Participants included infants and adults ages 25 to 64 years with selected causes of death (1999 to 2006). Exposures included that residential segregation and race-specific social deprivation variables. Main outcome measures were obtained via principal components analyses with an orthogonal rotation to identify a common factor. To discern whether the common factor was socially mediated, negative binomial multiple regression models were developed for which the dependent variable was the common factor. Results showed that infant deaths, mortality from assault, and malignant neoplasm of the trachea, bronchus and lung formed a common factor for race-gender groups (black/white and men/women). Regression analyses showed statistically significant, positive associations between low socio-economic status for all race-gender groups and this common factor.
Between 1999 and 2006, deaths classified as "assault" and "lung cancer", as well as "infant mortality" formed a socially mediated factor detectable in population but not individual data. Despite limitations related to death certificate data, the results contribute important information to the formulation of several hypotheses: (a) disease classifications based on anatomic or etiologic criteria fail to account for social determinants; (b) social forces produce demographically and possibly geographically distinct population-based disease constellations; and (c) the individual components of population-based disease constellations (e.g., lung cancer) are phenotypically comparable from one population to another but genotypically different, in part, because of socially mediated epigenetic variations. Additional research may produce new taxonomies that unify social determinants with anatomic and/or etiologic determinants. This may lead to improved medical management of individuals and populations.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
There is a tremendous need for coordinated, accessible mental health services for people with serious mental illness who are in contact, or at high risk of involvement, with the criminal justice ...system. Despite inadequate equipment and personnel, the Texas criminal justice system increasingly provides care for individuals with serious mental illness. Lubbock County Detention Center (LCDC) serves as a regional hub for inmate detention in rural west Texas, providing criminal justice and mental health services across a 250-mile radius. Nearly 50% of LCDC inmates have a history of mental illness. To address gaps in care for justice-involved individuals with serious mental illness, LCDC, Texas Tech University, Texas Tech University Health Sciences Center, and Starcare (a mental health regional provider) formed a justice and mental health collaborative (JMHC). JMHC first identified community organizations and collaborators who could contribute to a continuum of mental health care and services. In October 2017, JMHC received a US Department of Justice (DOJ) grant to evaluate efforts to reduce recidivism, divert individuals with serious mental illness from jail into treatment, and establish continuity of care.
Diversion: A Systems Theory Perspective Gittner, Lisaann S.; Dennis, Jeff A.; Forbis, Robert E.
Journal of contemporary criminal justice,
11/2023, Letnik:
39, Številka:
4
Journal Article
Recenzirano
There is a distinct lack of a normative theory for diversion of justice-involved individuals with mental illness at the intersection of the criminal justice and health care systems. The nexus where ...the criminal justice and health care systems are supposed to connect during diversion is not conceptually framed in a measurable way. The paper proposes a potential systems theory of diversion that explicates the overlapping boundaries within and between the criminal justice and health care systems. From a systems perspective, diversion is operationalized differently depending on the entry of an individual with justice involvement and mental illness into one of the systems. The criminal justice and health care systems have multiple levels (micro-, meso-, and macro-), but individuals enter both systems at the respective systems intersection of the micro- and meso-levels. The theoretical disconnect may fail to consider the impact of criminal justice diversion on the health care system. We propose a unified systems theory of diversion to improve evaluation, comparability, sustainability, resource allocation, and outcomes of diversion programs.
Introduction:
Although new COVID-19 cases have been decreasing globally, long-haul COVID-19 continues to present a challenge. Long-haul COVID-19 symptoms, such as dyspnea, fatigue, cognitive ...impairments, gastrointestinal distress, and mood changes, can remain for months after initial infection in 10-30% of individuals infected with COVID-19. These symptoms can limit daily function and decrease quality of life. Given the recency of the disease, very little literature exists on the causes of long-haul COVID-19 and few treatment options are available for afflicted individuals. This case report describes the use of the Eastern medicine practices of Tai Chi and Qigong as a possible technique to increase lung function and thus daily function in those with long-haul COVID. Both Tai Chi and Qigong were developed thousands of years ago in China and utilized as part of traditional Chinese medicine. They are forms of gentle, low-intensity exercise involving slow, continuous movements and stretches that focus on alignment, coordination, and breathing control. Previous studies have shown that Tai Chi and Qigong provide beneficial effects in those experiencing mood disorders, chronic pain, cardiovascular issues, fibromyalgia, and chronic obstructive pulmonary disease. Although practitioners have proposed the use of Tai Chi and Qigong in patients with COVID-19, no data exists on the outcomes.
Materials and Methods:
This case report presents a patient with pre-existing conditions of obesity, gastroesophageal reflux disease, cervical cancer, cataract surgery, and sinus surgery initially diagnosed with COVID-19 with symptoms of acute dyspnea, dizziness, cough, headache, chills, fever, rhinorrhea, and sore throat. She was later diagnosed with long-haul COVID-19 with symptoms of dyspnea, fatigue, and dizziness on exertion and gastrointestinal distress. The patient practiced Tai Chi and Qigong three to four times weekly for about 30 min on average.
Results:
The patient experienced decreases in resting heart rate and weight and an increase in oxygen saturation level (SpO2) from 83% to 96%, indicating that Tai Chi and Qigong may have the potential to restore lung function.
Conclusion:
Thus, we propose that Tai Chi and Qigong can be an easily accessible, low-intensity, and cost-effective technique to increase lung function and quality of life in patients with long-haul COVID-19.
Assess the psychometric properties of the Self-Efficacy Consumption of Fruit and Vegetable Scale (F/V scale) in African American women.
Midwestern Health Maintenance Organization.
221 African ...American women age 40–65 with BMI≥30
F/V scale was compared to eating efficacy/availability subscale reported on the WEL and mean micronutrient intake (vitamins A, C, K, folate, potassium, and beta-carotene reported on 3-day food records.
F/V scale construct validity and internal consistency were assessed and compared to: 1) the original scale validation in Chinese women, 2) WEL scale, and 3) to micronutrient intake from 3-day food records. Total scale scores differed between African American women (μ=1.87+/−0.87) and Chinese (μ=0.41). In a Chinese population, F/V scale factored into two subscales; the F/V factored into one subscale in African American women. Construct validity was supported with correlation between the F/V scale and the eating efficacy WEL subscale (r2=−0.336, p=0.000). There was not a significant correlation between dietary consumption of micronutrients representative of fruit and vegetable intake and the F/V scale.
The F/V scale developed for Chinese populations can be reliably used with African American women.
•Eating self-efficacy is important when performing obesity reduction interventions.•Measuring the belief in one's ability to eat healthy is critical for understanding eating behaviors.•There are very few constructs of eating self-efficacy.•The Fruit and Vegetable Scale is the only eating self-efficacy scale.•The Fruit and Vegetable Scale (F/V scale) is valid in American populations.
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Diversion: Where Do We Go From Here? Forbis, Robert E.; Gittner, Lisaann S.; Dennis, Jeff A. ...
Journal of contemporary criminal justice,
11/2023, Letnik:
39, Številka:
4
Journal Article
Recenzirano
This conclusion provides a brief synopsis of the research articles presented in this special edition of The Journal of Contemporary Justice. The research findings clearly demonstrate that when the ...objective of diversion is sought by diversion-based programs where the criminal justice and health care systems intersect, processes and services frequently break down. As this collection of articles highlights, our collective understanding of diversion is siloed by academic discipline; thus, the broader picture of diversion remains muddled. It remains muddled because the reporting of diversion is scattered across disciplinary journals where a more robust understanding of diversion becomes unwieldy if not impossible for researchers and practitioners alike without sifting through multiple books, journals, manuscripts, and websites. Therefore, diversion will continue to elude efficacy without the coordination and cooperation of numerous disciplines spanning both the criminal justice and health care systems diversion. As this collection of articles strongly suggests, there is a need to create a transdisciplinary understanding of diversion as well as publication outlets so best practices can be developed and shared in one place.
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