In this cross-sectional analysis of data from overweight or obese children and young adults from NHANES (1999–2012), severe obesity was associated with an increased prevalence of cardiometabolic risk ...factors, particularly in boys and young men.
The prevalence of severe obesity among children and young adults has increased in recent years
1
and has led to a heightened awareness and concern about the cardiovascular and metabolic health of persons in this age group. In 1999–2004, almost 4% of children and young adults in the United States 2 to 19 years of age were classified as having severe obesity,
2
and as recently as 2011–2012, the prevalence of severe obesity increased to approximately 6% in this age group
1
; however, the prevalence of cardiometabolic risk factors accompanying severe obesity in these children and young adults is unclear.
Cardiometabolic risk . . .
The purpose of the study was to examine (1) how patient adherence and eye drop technique were associated with visual field defect severity and (2) how general glaucoma adherence self-efficacy and eye ...drop technique self-efficacy were related to visual field defect severity.
Cross-sectional study conducted at a single private practice site.
Patients using eye drops for their glaucoma.
Subject adherence to glaucoma medications through Medication Events Monitoring System (MEMS) devices were measured, and eye drop instillation technique was assessed by video recording. General glaucoma medication adherence self-efficacy was measured using a 10-item scale, and eye drop technique self-efficacy was measured using a 6-item scale. Multivariate logistic regression was used to analyze the data.
Visual field defect severity.
Patients who were less than 80% adherent according to the MEMS devices were significantly more likely to have worse defect severity. Patients with lower scores on the general glaucoma medication adherence self-efficacy scale also were significantly more likely to have worse defect severity. Eye drop technique and eye drop technique self-efficacy were not related significantly to visual field defect severity.
Eye care providers need to assess patient adherence and to work with those patients with poor adherence to find ways to improve their ability and self-efficacy in using their glaucoma medications.
Proprietary or commercial disclosure may be found after the references.
The American Academy of Pediatrics (AAP) recommends children in foster care (FC) have an initial medical evaluation within 3 days of custody initiation; however, this vulnerable population often ...suffers from disjointed care. Our aim was to improve the mean time to initial foster care evaluation (TIE) from 32 to <7 days within 12 months for children in FC in Durham County, North Carolina.
This study was a time series, quality improvement project used to target interventions within an academic clinic and a community agency. Interventions were tested through multiple plan-do-study-act cycles. Control charts of the primary outcome, the TIE, were constructed. Charts were annotated with the dates of interventions, including workshops, performance feedback, integration of state forms, identification of appointments, development of an urgent appointment pathway, and empowerment of the scheduler.
The mean TIE improved from 32 to 9 days within 12 months. Significant improvement in the following 2 process measures contributed to this: the time from custody initiation to the referral date improved from an average of 10 to 3 days, and the time from referral date to the initial evaluation improved from an average of 22 to 6 days.
Improvement interventions and increased collaboration between medical and child welfare agencies can result in significant improvement of the TIE. However, despite improvement efforts, challenges remain in meeting the AAP 3-day TIE recommendation. We recommend further assessment of the AAP guideline as it relates to implementation feasibility and health outcomes of children in FC.
Objective
Provide the most recent data on the prevalence of obesity and severe obesity among United States children and adolescents aged 2 to 19 years.
Methods
The National Health and Nutrition ...Examination Survey, 1999–2014, was used. Weight status was defined using measured height and weight and standard definitions as follows: overweight as ≥85th percentile for age‐ and sex‐specific BMI; class I obesity as ≥95th percentile; class II obesity as ≥120 of the 95th percentile, or BMI ≥35; and class III obesity as ≥140% of the 95th percentile, or BMI ≥40. This study reports the prevalence of obesity by 2‐year National Health and Nutrition Examination Survey cycle and Wald tests comparing the 2011–2012 cycle with the 2013–2014 cycle, as well as the linear trend from 1999 to 2014. Multivariable logistic regression models estimated odds ratios for differences by each 2‐year cycle.
Results
In 2013–2014, 17.4% of children met criteria for class I obesity, including 6.3% for class II and 2.4% for class III, none statistically different than 2011–2012. A clear, statistically significant increase in all classes of obesity continued from 1999 through 2014.
Conclusions
There is no evidence of a decline in obesity prevalence in any age group, despite substantial clinical and policy efforts targeting the issue.
Obesity is associated with poorer youth fitness. However, little research has examined the magnitude of this relationship in youth with severe obesity. Therefore, we sought to determine the ...relationship between increasing weight status and fitness within a sample of children and adolescents from New York City public schools.
This study utilized longitudinal data from the NYC Fitnessgram dataset years 2010-2018. Height and weight along with fitness were measured annually during physical education classes. Severity of obesity was defined using body mass index relative to the 95th percentile and then categorized into classes. A composite measure of fitness was calculated based on scores for three fitness tests: aerobic capacity, muscular strength, and muscular endurance. To examine the weight status-fitness relationship, repeated measures mixed models with random-intercepts were constructed. Stratified models examined differences by demographic factors.
The sample included 917,554 youth (51.8% male, 39.3% Hispanic, 29.9% non-Hispanic Black, 14.0%, 4.6%, and 1.6% class I, II and III obesity, respectively). Compared to youth with healthy weight, increasing severity of obesity was associated with decreased fitness: overweight (β = - 0.28, 95% CI:-0.29;-0.28), class I obesity (β = - 0.60, 95% CI:-0.60; - 0.60), class II obesity (β = - 0.94, 95% CI:-0.94; - 0.93), and class III obesity (β = - 1.28; 95% CI:-1.28; - 1.27). Stratified models showed the association was stronger among male and non-Hispanic White youth.
Findings revealed that more severe obesity was associated with lower fitness. Future research is needed to develop targeted interventions to improve fitness in youth with obesity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Purpose
This review sought to (a) describe definitions of long‐term opioid therapy (LTOT) outcome measures, and (b) identify the predictors associated with the transition from short‐term opioid use ...to LTOT for opioid‐naïve individuals.
Methods
We conducted a systematic review of the peer‐reviewed literature (January 2007 to July 2018). We included studies examining opioid use for more than 30 days. We classified operationalization of LTOT based on criteria used in the definitions. We extracted LTOT predictors from multivariate models in studies of opioid‐naïve individuals.
Results
The search retrieved 5,221 studies, and 34 studies were included. We extracted 41 unique variations of LTOT definitions. About 36% of definitions required a cumulative duration of opioid use of 3 months. Only 17% of definitions considered consecutive observation periods, 27% used days' supply, and no definitions considered dose.
We extracted 76 unique predictors of LTOT from seven studies of opioid‐naïve patients. Common predictors included pre‐existing comorbidities (21.1%), non‐opioid prescription medication use (13.2%), substance use disorders (10.5%), and mental health disorders (10.5%).
Conclusions
Most LTOT definitions aligned with the chronic pain definition (pain more than 3 months), and used cumulative duration of opioid use as a criterion, although most did not account for consistent use. Definitions were varied and rarely accounted for prescription characteristics, such as days' supply. Predictors of LTOT were similar to known risk factors of opioid abuse, misuse, and overdose. As LTOT becomes a central component of quality improvement efforts, researchers should incorporate criteria to identify consistent opioid use to build the evidence for safe and appropriate use of prescription opioids.
The objective of this technical report is to provide clinicians with evidence-based, actionable information upon which to make assessment and treatment decisions for children and adolescents with ...obesity. In addition, this report will provide an evidence base to inform clinical practice guidelines for the management and treatment of overweight and obesity in children and adolescents. To this end, the goal of this report was to identify all relevant studies to answer 2 overarching key questions: (KQ1) "What are clinically based, effective treatments for obesity?" and (KQ2) "What is the risk of comorbidities among children with obesity?" See Appendix 1 for the conceptual framework and a priori key questions.
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