Report card on school snack food policies among the United States' largest school districts in 2004–2005: Room for improvement

BACKGROUND: Federal nutritional guidelines apply to school foods provided through the national school lunch and breakfast programs, but few federal regulations apply to other foods and drinks sold in schools (labeled "competitive foods"), which are often high in calories, fat and sugar. Competitive food policies among school districts are increasingly viewed as an important modifiable factor in the school nutrition environment, particularly to address rising rates of childhood overweight. Congress passed legislation in 2004 requiring all school districts to develop a Wellness Policy that includes nutrition guidelines for competitive foods starting in 2006–2007. In addition, the Institute of Medicine (IOM) recently published recommendations for schools to address childhood obesity. METHODS: Representatives of school districts with the largest student enrollment in each state and D.C. (N = 51) were interviewed in October-November 2004 about each school district's nutrition policies on "competitive foods." District policies were examined and compared to the Institute of Medicine's recommendations for schools to address childhood obesity. Information about state competitive food policies was accessed via the Internet, and through state and district contacts. RESULTS: The 51 districts accounted for 5.9 million students, representing 11% of US students. Nineteen of the 51 districts (39%) had competitive food policies beyond state or federal requirements. The majority of these district policies (79%) were adopted since 2002. School district policies varied in scope and requirements. Ten districts (53%) set different standards by grade level. Most district policies had criteria for food and beverage content (74%) and prohibited the sale of soda in all schools (63%); fewer policies restricted portion size of foods (53%) or beverages (47%). Restrictions more often applied to vending machines (95%), cafeteria à la carte (79%), and student stores (79%) than fundraising activities (47%). Most of the policies did not address more comprehensive approaches to the school nutrition environment, such as nutrition education (32%) or advertising to students (26%), nor did they include guidelines on physical education (11%). In addition, few policies addressed monitoring (32%) or consequences for non-compliance (11%). No policy restricted foods sold for after-school fundraising or required monitoring physical health indicators (e.g. BMI). CONCLUSION: When compared to the Institute of Medicine's recommendations for schools' role in preventing obesity, none of the nutrition policies among each state's largest school district had addressed all the recommendations by 2004–2005. Nutritionists, nurses, pediatricians, parents, and others concerned about child health have an unprecedented opportunity to help shape and implement more comprehensive school district nutrition policies as part of the Congressional requirement for a "Wellness Policy" by 2006–2007

Alcohol Interventions for Trauma Patients Treated in Emergency Departments and Hospitals: A Cost Benefit Analysis

Summarizes a study of whether screening for problem drinking and interventions to reduce alcohol intake in hospital trauma centers reduce the direct cost of injury-related health care. Compares the costs of injury recidivism with and without intervention

History of dating violence and the association with late adolescent health

BACKGROUND: The present investigation expands upon prior studies by examining the relationship between health in late adolescence and the experience of physical/sexual and non-physical dating violence victimization, including dating violence types that are relevant to today’s adolescents (e.g., harassment via email and text messaging). We examined the relationship between physical/sexual and non-physical dating violence victimization from age 13 to 19 and health in late adolescence/early adulthood. METHODS: The sample comprised 585 subjects (ages 18 to 21; mean age, 19.8, SD = 1.0) recruited from The Ohio State University who completed an online survey to assess: 1) current health (depression, disordered eating, binge drinking, smoking, and frequent sexual behavior); and 2) dating violence victimization from age 13 to 19 (retrospectively assessed using eight questions covering physical, sexual, and non-physical abuse, including technology-related abuse involving stalking/harassment via text messaging and email). Multivariable models compared health indicators in never-exposed subjects to those exposed to physical/sexual or non-physical dating violence only. The multivariable models were adjusted for age and other non-dating abuse victimization (bullying; punched, kicked, choked by a parent/guardian; touched in a sexual place, forced to touch someone sexually). RESULTS: In adjusted analyses, compared to non-exposed females, females with physical/sexual dating violence victimization were at increased risk of smoking (prevalence ratio = 3.95); depressive symptoms (down/hopeless, PR = 2.00; lost interest, PR = 1.79); eating disorders (using diet aids, PR = 1.98; fasting, PR = 4.71; vomiting to lose weight, PR = 4.33); and frequent sexual behavior (5+ intercourse and oral sex partners, PR = 2.49, PR = 2.02; having anal sex, PR = 2.82). Compared to non-exposed females, females with non-physical dating violence only were at increased risk of smoking (PR = 3.61), depressive symptoms (down/hopeless, PR = 1.41; lost interest, PR = 1.36), eating disorders (fasting, PR = 3.37; vomiting, PR = 2.66), having 5+ intercourse partners (PR = 2.20), and having anal sex (PR = 2.18). For males, no health differences were observed for those experiencing physical/sexual dating violence compared to those who did not. Compared to non-exposed males, males with non-physical dating violence only were at increased risk of smoking (PR = 3.91) and disordered eating (fasting, using diet aids, vomiting, PR = 2.93). CONCLUSIONS: For females, more pronounced adverse health was observed for those exposed to physical/sexual versus non-physical dating violence. For both females and males, non-physical dating violence victimization contributed to poor health

A novel approach to assessment of US pediatric trauma system development.

Importance Mature trauma systems are critical in building and maintaining national, state, and local resilience against all-hazard disasters. Currently, pediatric state trauma system plans are not standardized and thus are without concrete measures of potential effectiveness. Objective To develop objective measures of pediatric trauma system capability at the state level, hypothesizing significant variation in capabilities between states, and to provide a contemporary report on the status of national pediatric trauma system planning and development. Design, Setting, and Participants A national survey was deployed in 2018 to perform a gap analysis of state pediatric trauma system capabilities. Four officials from each state were asked to complete the survey regarding extensive pediatric-related or specific trauma system parameters. Using these parameters, a panel of 14 individuals representing national stakeholder sectors in pediatric trauma care convened to identify the essential components of the ideal pediatric trauma system using Delphi methodology. Data analysis was conducted from March 16, 2019, to February 23, 2020. Main Outcomes and Measures Based on results from the national survey and consensus panel parameters, each state was given a composite score. The score was validated using US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) fatal injury database. Results The national survey had less than 10% missing data. The consensus panel reached agreement on 6 major domains of pediatric trauma systems (disaster, legislation/funding, access to care, injury prevention/recognition, quality improvement, pediatric readiness) and was used to develop the Pediatric Trauma System Assessment Score (PTSAS) based on 100 points. There was substantial variation across states, with state scores ranging from 48.5 to 100. Based on US CDC WONDER data, for every 1-point increase in PTSAS, there was a 0.12 per 100 000 decrease in mortality (95% CI, −0.22 to −0.02; P = .03). Conclusions and Relevance Results of this cross-sectional study suggest that a more robust pediatric trauma system has a significant association with pediatric injury mortality. This study assessed the national landscape of capability and preparedness to provide pediatric trauma care at the state level. These parameters can tailor the maturation of children’s interests within a state trauma system and assist with future state, regional, and national planning

Demographic patterns and outcomes of patients in level I trauma centers in three international trauma systems

Introduction: Trauma systems were developed to improve the care for the injured. The designation and elements comprising these systems vary across countries. In this study, we have compared the demographic patterns and patient outcomes of Level I trauma centers in three international trauma systems. Methods: International multicenter prospective trauma registry-based study, performed in the University Medical Center Utrecht (UMCU), Utrecht, the Netherlands, John Hunter Hospital (JHH), Newcastle, Australia, and Harborview Medical Center (HMC), Seattle, the United States. Inclusion: patients =18 years, admitted in 2012, registered in the institutional trauma registry. Results: In UMCU, JHH, and HMC, respectively, 955, 1146, and 4049 patients met the inclusion criteria of which 300, 412, and 1375 patients with Injury Severity Score (ISS) > 15. Mean ISS was higher in JHH (13.5; p < 0.001) and HMC (13.4; p < 0.001) compared to UMCU (11.7). Unadjusted mortality: UMCU = 6.5 %, JHH = 3.6 %, and HMC = 4.8 %. Adjusted odds of death: JHH = 0.498 [95 % confidence interval (CI) 0.303-0.818] and HMC = 0.473 (95 % CI 0.325-0.690) compared to UMCU. HMC compared to JHH was 1.002 (95 % CI 0.664-1.514). Odds of death patients ISS > 15: JHH = 0.507 (95 % CI 0.300-0.857) and HMC = 0.451 (95 % CI 0.297-0.683) compared to UMCU. HMC = 0.931 (95 % CI 0.608-1.425) compared to JHH. TRISS analysis: UMCU: Ws = 0.787, Z = 1.31, M = 0.87; JHH, Ws = 3.583, Z = 6.7, M = 0.89; HMC, Ws = 3.902, Z = 14.6, M = 0.84. Conclusion: This study demonstrated substantial differences across centers in patient characteristics and mortality, mainly of neurological cause. Future research must investigate whether the outcome differences remain with nonfatal and long-term outcomes. Furthermore, we must focus on the development of a more valid method to compare systems

Withdrawal of Life-Sustaining Therapy in Injured Patients: Variations Between Trauma Centers and Nontrauma Centers

Background—We sought to identify patient and institutional variables predictive of a withdrawal of care order (WOCO) in trauma patients. We hypothesized that the frequency of WOCO would be higher at trauma centers. Methods—Data from the National Study on the Costs and Outcomes of Trauma (NSCOT) was used to determine associations between WOCO status and patient characteristics, institutional characteristics, and hospital course. Chi-square, t-tests and multivariate analysis was used to identify variables predictive of WOCO. Results—Of 14,190 patients, 618 (4.4%) had WOCO, which accounted for 60.9% of patients who died in hospital. Age (p=<0.001), race (p=<0.001), co-morbidity (p=<0.001) and injury mechanism were associated with WOCO (p=0.03). WOCO patients had higher NISS (p=<0.001), lower GCS motor scores (p=<0.001) and higher incidence of midline shift on head CT (p=0.01). Trauma center status (OR 1.56 (95% CI 1.06,2.30)) and closed ICU (OR 1.53 (95% CI 1.03,2.25)) were also predictive of WOCO. There was sizeable variation (0 to 16%) in the percentage of patients with WOCO across centers. Conclusion—Most trauma patients who die in hospital do so after a WOCO. Although trauma center status and closed ICU are predictive of WOCO, variation in the percentage of patients with WOCO across all centers speaks to the complexity of these decisions. Further investigation is needed to understand how WOCO is applied to trauma patients