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The authors reflect on the issues and problems regarding injuries in the pediatric athlete in the U.S. They argue that injuries in pediatric athletes are the results of improper technique, poorly fitting protective equipment, training errors, muscle weakness and growth imbalance. They suggest that in order to reduce the risk of sports and recreation-related injuries, one must have personal countermeasures, behavioral interventions, and environmental modifications.

Context: Field hockey is popular worldwide; however, it entails a risk of injury. Injuries hamper players' participation in the sport and impose a burden on public health., Objective: To investigate the effectiveness of a structured exercise program among youth field hockey players on the injury rate, severity, and burden., Design: Quasi-experimental study., Setting: On field during 1 season of field hockey (October 2016 through June 2017)., Patients or Other Participants: A convenience sample of 22 teams (291 players): 10 teams (135 players, mean age = 11.5 years [95% confidence interval (CI) = 11.2, 11.7 years]) in the intervention group and 12 teams (156 players, mean age = 12.9 years [95% CI = 12.6, 13.2 years]) in the control group., Intervention(s): The Warming-up Hockey program, a sex- and age-specific, structured, evidence-informed warm-up program consisting of a preparation phase (ie, agility and cardiovascular warm-up exercises), movement skills (ie, stability and flexibility exercises), and sport-specific skills (ie, speed and strength exercises in field hockey situations). Participants in the control group performed their usual warm-up routines., Main Outcome Measure(s): Injury rate (ie, the number of injuries per 1000 player-hours of field hockey exposure), severity (ie, days of player time-loss), and burden on athletes' availability to play (ie, days of time loss due to injury per 1000 player-hours of field hockey exposure)., Results: The injury rate was lower in the intervention group (hazard ratio of 0.64 [95% CI = 0.38, 1.07]); however, this result was not statistically significant. The severity of injuries was similar in both groups ( t statistic P = .73). The burden of injuries on players' field hockey participation was lower in the intervention group (difference of 8.42 [95% CI = 4.37, 12.47] days lost per 1000 player-hours of field hockey)., Conclusions: Exposure to the Warming-up Hockey program was not significantly associated with a lower injury rate. No reduction was observed in the severity of injuries alone; however, the burden of injuries on players' field hockey participation was lower in the intervention group.

Objective: Using a standardized quality criteria list, we appraised the methodological quality of economic evaluations of occupational safety and health (OSH) interventions conducted from a corporate perspective., Methods: The primary literature search was conducted in Medline and Embase. Supplemental searches were conducted in the Cochrane NHS Economic Evaluation Database, the National Institute for Occupational Safety and Health (NIOSH) database, the Ryerson International Labour, Occupational Safety and Health Index, scans of reference lists, and researchers' own literature database. Independently, two researchers selected articles based on title, keywords, and abstract, and if needed, fulltext. Disagreements were resolved by a consensus procedure. Articles were selected based on seven criteria addressing study population, type of intervention, comparative intervention, outcome, costs, language, and perspective. Two reviewers independently judged methodological quality using the Consensus on Health Economic Criteria (CHEC-list), a 19-item standardized quality criteria list. Disagreements in judgment were also resolved by consensus. Data were analyzed descriptively., Results: A total of 34 studies were included. Of these, only 44% of the studies met more than 50% of the quality criteria. Of the 19 quality criteria, 8 were met by 50% or more of the studies. The 11 least fulfilled criteria related to (i) performance of a sensitivity analysis, (ii) selection of perspective, (iii) description of study population, (iv) discussion of generalizability, (v) description of competing alternatives, (vi) presentation of the research question, (vii) measurement of outcomes, (viii) measurement of costs, (ix) valuation of costs, (x) declaration of researchers' independence, and (xi) discussion of ethical and distributional issues., Conclusions: Apart from a few exceptions, the overall methodological quality of the economic evaluations of OSH interventions from a corporate perspective was poor. As such, there is a risk of biased results. The quality of future evaluations needs to be improved to increase the validity of their conclusions and recommendations.

Objective: Factors associated with weight gain during pregnancy that may be linked to maternal overweight and obesity were examined., Methods: In this observational study, 144 women reported on demographics, (prepregnancy) body weight, and lifestyles in self-reported questionnaires at 30 weeks gestation. Body weight at the end of pregnancy (self-reported at 6 weeks postpartum) was used to determine total gestational weight gain. Multivariate prediction models were developed to identify factors associated with total gestational weight gain and excessive gestational weight gain (i.e., higher weight gain than recommended by the Institute of Medicine)., Results: Women gained 14.4 (+/-5.0) kg during pregnancy. Obese women gained almost 4 kg less than normal weight women. Pregnant women judging themselves to be less physically active or women who reported increased food intakes during pregnancy gained significantly more weight. Over one third of women (38%) gained more weight than recommended. Being overweight, judging yourself to be less physically active than others, and a perceived elevated food intake during pregnancy were significantly associated with excessive weight gain (odds ratio [OR] = 6.33, 95% confidence interval [CI]: 2.01-19.32; OR = 3.96, 95% CI: 1.55l, 10.15; and OR = 3.14, 95% CI: 1.18, 8.36, respectively). A higher age at menarche and hours of sleep reduced the odds for excessive weight gain (OR = 0.75, 95% CI: 0.57, 0.99; and OR = 0.35, 95% CI: 0.57, 0.93, respectively)., Conclusions: Mean hours of sleep, perceived physical activity, and measures of food intake at 30 weeks gestation were identified as modifiable behavioral correlates for excessive gestational weight gain. Strategies to optimize gestational weight gain need to be explored, with a focus on the identified factors.