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Lee Child Personal Epub 15

OBJECT Sport-related concussion (SRC) is a major public health problem. Approximately 90% of SRCs in high school athletes are transient; symptoms recover to baseline within 1 week. However, a small percentage of patients remain symptomatic several months after injury, with a condition known as postconcussion syndrome (PCS). The authors aimed to identify risk factors for PCS development in a cohort of exclusively young athletes (9-18 years of age) who sustained SRCs while playing a sport. METHODS The authors conducted a retrospective case-control study by using the Vanderbilt Sports Concussion Clinic database. They identified 40 patients with PCS and matched them by age at injury and sex to SRC control patients (1 PCS to 2 control). PCS patients were those experiencing persistent symptoms at 3 months after an SRC. Control patients were those with documented resolution of symptoms within 3 weeks of an SRC. Data were collected in 4 categories: 1) demographic variables; 2) key medical, psychiatric, and family history; 3) acute-phase postinjury symptoms (at 0-24 hours); and 4) subacute-phase postinjury features (at 0-3 weeks). The chi-square Fisher exact test was used to assess categorical variables, and the Mann-Whitney U-test was used to evaluate continuous variables. Forward stepwise regression models (Pin = 0.05, Pout = 0.10) were used to identify variables associated with PCS. RESULTS PCS patients were more likely than control patients to have a concussion history (p = 0.010), premorbid mood disorders (p = 0.002), other psychiatric illness (p = 0.039), or significant life stressors (p = 0.036). Other factors that increased the likelihood of PCS development were a family history of mood disorders, other psychiatric illness, and migraine. Development of PCS was not predicted by race, insurance status, body mass index, sport, helmet use, medication use, and type of symptom endorsement. A final logistic regression analysis of candidate variables showed PCS to be predicted by a history of concussion (OR 1.8, 95% CI 1.1-2.8, p = 0.016), preinjury mood disorders (OR 17.9, 95% CI 2.9-113.0, p = 0.002), family history of mood disorders (OR 3.1, 95% CI 1.1-8.5, p = 0.026), and delayed symptom onset (OR 20.7, 95% CI 3.2-132.0, p < 0.001). CONCLUSIONS In this age- and sex-matched case-control study of risk factors for PCS among youth with SRC, risk for development of PCS was higher in those with a personal and/or family history of mood disorders, other psychiatric illness, and migraine. These findings highlight the unique nature of SRC in youth. For this population, providers must recognize the value of establishing the baseline health and psychiatric status of children and their primary caregivers with regard to symptom reporting and recovery expectations. In addition, delayed symptom onset was an unexpected but strong risk factor for PCS in this cohort. Delayed symptoms could potentially result in late removal from play, rest, and care by qualified health care professionals. Taken together, these results may help practitioners identify young athletes with concussion who are at a greater danger for PCS and inform larger prospective studies for validation of risk factors from this cohort.

Worldwide, the prevalence of obesity among children has increased dramatically. Although the etiology of childhood obesity is multifactorial, to date, most preventive interventions have focused on school-aged children in school settings and have met with limited success. In this review, we focus on another set of influences that impact the development of children's eating and weight status: parenting and feeding styles and practices. Our review has two aims: (1) to assess the extent to which current evidence supports the hypothesis that parenting, via its effects on children's eating, is causally implicated in childhood obesity; and (2) to identify a set of promising strategies that target aspects of parenting, which can be further evaluated as possible components in childhood obesity prevention.

A literature review was conducted between October 2006 and January 2007. Studies published before January 2007 that assessed the association between some combination of parenting, child eating and child weight variables were included.

A total of 66 articles met the inclusion criteria. The preponderance of these studies focused on the association between parenting and child eating. Although there was substantial experimental evidence for the influence of parenting practices, such as pressure, restriction, modeling and availability, on child eating, the majority of the evidence for the association between parenting and child weight, or the mediation of this association by child eating, was cross-sectional.

To date, there is substantial causal evidence that parenting affects child eating and there is much correlational evidence that child eating and weight influence parenting. There are few studies, however, that have used appropriate meditational designs to provide causal evidence for the indirect effect of parenting on weight status via effects on child eating. A new approach is suggested for evaluating the effectiveness of intervention components and creating optimized intervention programs using a multiphase research design. Adoption of approaches such as the Multiphase Optimization Strategy (MOST) is necessary to provide the mechanistic evidence-base needed for the design and implementation of effective childhood obesity prevention programs.

Given this lack of success, an expansion of prevention approaches to other contexts and younger age groups is warranted. Given that a significant proportion of children are already overweight prior to school entry, a focus on young children and the home and child-care settings where they live provide alternative contexts for obesity prevention. The family is the primary social institution influencing young children, thus, it is likely that many modifiable risk factors for childhood obesity have substantial roots within the family context.

Although evidence on how the family context influences childhood obesity is still limited, research examining caregivers' influence on young children's eating and weight status has increased dramatically in recent years, from one or two studies per year in 1975 and 1999 to about 15 studies published in 2006 alone. The objective of this review is to summarize and evaluate the evidence for the influence of parents and caregivers on the development children's eating and weight status. Additionally, by reviewing and critically assessing the literature currently available on this topic, we aim to provide new insights to inform the design of obesity primary prevention efforts.

Figure 1 presents a model depicting pathways of influence among three key constructs: parenting, child eating, and child weight. This model will be more fully developed below, but in brief, parenting encompasses parenting and feeding styles and practices, child eating encompasses children's eating style, food preferences and dietary intake and child weight encompasses indices of children's weight status or change in weight status. For the purposes of this review, this model is limited to the influence of parenting on children's eating and weight, yet a similar model could be applied to depict relations among parenting, children's physical activity and weight status.

A conceptual mediation model for the influence of parenting and feeding practices and styles on children's eating behavior, dietary preferences, intake and subsequent weight status. Note: A total of 67 studies were reviewed, the numbers under the pathway labels indicate the proportion of studies that addressed that given pathway. Fourty-nine studies addressed one pathway, 14 studies addressed two pathways and only 4 studies addressed all three pathways. Note that because some studies addressed more than one pathway, the n's presented in the figure add up to more than 67. The majority of studies (34) utilized cross-sectional designs; 11 of studies were longitudinal and 21 used experimental designs to manipulate (or simulate manipulation of) parenting.

The critical question to be addressed using this model is: "How does parenting influence a child's weight?" The pathways in the model represent links among three constructs involved in answering this question: Pathway 1 addresses the association between parenting and child weight, Pathway 2 addresses the association between parenting and child eating and Pathway 3 addresses the association between child eating and child weight.

There are two major implications of this model that, as will be illustrated below, many of the studies currently available fail to embrace. The first implication of this model is that the arrows between constructs indicate that no association between constructs in this model is unidirectional. Parenting influences child eating and weight, but child eating and weight also influence parenting. We argue that despite the tendency of many researchers to assign direction when interpreting cross-sectional findings (specifically, that the parent is influencing the child), the direction of any association found between the constructs in this model cannot be determined on the basis of cross-sectional evidence; bidirectionality is more likely, especially when parent-child interactions are the focal point [6]. Only properly designed longitudinal and experimental studies can provide evidence for direction of influence. The second implication is that the model specifies mediation; we argue that, logically, parenting cannot have direct effects on child weight. Parents influence child weight directly through genetics, but we argue that the influence of parenting on child weight must be mediated by effects of parenting on child eating (or other child behaviors). Therefore, at minimum, researchers need to include measures of parenting, child weight and child eating in study designs if they desire to accurately explain how parenting affects child weight. In contrast, a direct association between child weight and parenting is a logical possibility, as child weight can influence what parenting practices are used. If this is the research question of focus, a design with just parenting and child weight status variables will suffice. 2b1af7f3a8

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