Importance: Refugees and internally displaced persons are highly vulnerable to sexual violence during conflict and subsequent displacement. However, accurate estimates of the prevalence of sexual violence among in these populations remain uncertain. Objective: Our objective was to estimate the prevalence of sexual violence among refugees and displaced persons in complex humanitarian emergencies. Data Source: We conducted systematic review of relevant literature in multiple databases (EMBASE, CINAHL, and MEDLINE) through February 2013 to identify studies. We also reviewed reference lists of included articles to identify any missing sources. Study Selection: Inclusion criteria required identification of sexual violence among refugees and internally displaced persons or those displaced by conflict in complex humanitarian settings. Studies were excluded if they did not provide female sexual violence prevalence, or that included only single case reports, anecdotes, and those that focused on displacement associated with natural disasters. After a review of 1175 citations 19 unique studies were selected. Data Extraction: Two reviewers worked independently to identify final selection and a third reviewer adjudicated any differences. Descriptive and quantitative information was extracted; prevalence estimates were synthesized. Heterogeneity was assessed using I2. Main Outcomes: The main outcome of interest was sexual violence among female refugees and internally displaced persons in complex humanitarian settings. Results: The prevalence of sexual violence was estimated at 21.4% (95% CI, 14.9-28.7; I2=98.3%), using a random effects model. Statistical heterogeneity was noted with studies using probability sampling designs reporting lower prevalence of sexual violence (21.0%, 95% CI, 13.2-30.1; I2=98.6%), compared to lower quality studies (21.7%, 95% CI, 11.5-34.2; I2=97.4%). We could not rule out the presence of publication bias. Conclusions: The findings suggest that approximately one in five refugees or displaced women in complex humanitarian settings experienced sexual violence. However, this is likely an underestimation of the true prevalence given the multiple existing barriers associated with disclosure. The long-term health and social consequences of sexual violence for women and their families necessitate strategies to improve identification of survivors of sexual violence and increase prevention and response interventions in these complex settings.

No abstract

No abstract

No abstract

Increasing physical activity among children is a potentially important public health intervention. Quantifying the economic and health effects of the intervention would help decision makers understand its impact and priority. Using a computational simulation model that we developed to represent all US children ages 8–11 years, we estimated that maintaining the current physical activity levels (only 31.9 percent of children get twenty-five minutes of high-calorie-burning physical activity three times a week) would result each year in a net present value of $1.1 trillion in direct medical costs and $1.7 trillion in lost productivity over the course of their lifetimes. If 50 percent of children would exercise, the number of obese and overweight youth would decrease by 4.18 percent, averting $8.1 billion in direct medical costs and $13.8 billion in lost productivity. Increasing the proportion of children who exercised to 75 percent would avert $16.6 billion and $23.6 billion, respectively.

Systems modeling represents an innovative approach for addressing the obesity epidemic at the community level. We developed an agent-based model of the Baltimore City food environment that permits us to assess the relative impact of different programs and policies, alone and in combination, and potential unexpected consequences. Based on this experience, and a review of literature, we have identified a set of principles, potential benefits, and challenges. Some of the key principles include the importance of early and multilevel engagement with the community prior to initiating model development and continued engagement and testing with community stakeholders. Important benefits include improving community stakeholder understanding of the system, testing of interventions before implementation, and identification of unexpected consequences. Challenges in these models include deciding on the most important, yet parsimonious factors to consider, how to model food source and food selection behavior in a realistic yet transferable manner, and identifying the appropriate outcomes and limitations of the model.

Agent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence. Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact.

Objective This paper estimates specific additional disease outcomes and costs that could be saved from helping a patient go from obese to overweight to normal weight category at different ages. This information could help physicians, other health care workers, patients, and third party payers determine how to prioritize weight reduction. Methods We developed a computational Markov model that represented the BMI status, chronic health states, health outcomes, and associated costs (from various perspectives) as an adult ages throughout his/her lifetime. Results We calculated incremental costs of adult patients with obesity or overweight (versus normal weight) at different starting ages. For example, for a metabolically healthy 20-year old, being obese (versus normal weight) added lifetime third-party payer costs averaging $14,059(95% range: $13,956–$14,163), productivity losses of $14,141($13,969–$14,312), and total societal costs of $28,020($27,751–$28,289); being overweight versus normal weight added $5,055($4,967–$5,144), $5,358($5,199–$5,518), and $10,365($10,140–$10,590). For a metabolically healthy 50-year old, being obese added $15,925($15,831–$16,020), $20,120($19,887–$20,352), and $36,278($35,977–$36,579); being overweight added $5,866($5,779–$5,953), $10,205($9,980–$10,429), and $16,169($15,899–$16,438). Conclusions Incremental lifetime costs of a patient with obesity or overweight (versus normal weight) increased with the patient’s age, peaking at age 50, and decreasing with older ages. However, weight reduction even in older adults still yielded incremental cost savings.