Bettylou Sherry

Trends in the Prevalence of Extreme Obesity Among US Preschool-Aged Children Living in Low-Income Families, 1998-2010

rently 4 states (Minnesota, Oregon, Idaho, and North Carolina) allow MOC to count in lieu of continuing medical education for relicensing (and a number of others are moving in that direction), and participation in MOC can result in increased reimbursement through the Physician Quality and Reporting System program. The fees charged for certification and MOC go to support the complex assessment tools, for testing of the information technology platform, and for the rigorous quality standards needed for 19 different subspecialties as well as general medicine. The ABIM works hard to keep fee increases to a minimum and is proud that it charges the second lowest fees of all 24 boards.

Sociodemographic characteristics, care, feeding practices, and growth of cohorts of children born to HIV-1 seropositive and seronegative mothers in Nairobi, Kenya.

objectives To compare sociodemographic profiles, child care, child feeding practices and growth indices of children born to HIV‐1 seropositive and seronegative mothers.

Childhood obesity task forces established by state legislatures, 2001-2010.

Introduction States and communities are considering policy and environmental strategies, including enacting legislation, to reduce and prevent childhood obesity. One legislative approach has been to create task forces to understand key issues and develop a course of action. The goal of this study was to describe state-level, childhood obesity task forces in the United States created by legislation from 2001 through 2010. Methods We used the Center for Disease Control and Prevention’s Division of Nutrition, Physical Activity, and Obesity database to identify state-level childhood obesity task forces created through legislation from 2001 through 2010. Results We identified 21 states that had enacted legislation creating childhood obesity task forces of which 6 had created more than one task force. Most task forces were charged with both gathering and reviewing information and making recommendations for obesity-prevention actions in the state. Most legislation required that task forces include representation from the state legislature, state agencies, community organizations, and community members. Conclusion Evaluation of the effectiveness of obesity-prevention task forces and the primary components that contribute to their success may help to determine the advantages of the use of such strategies in obesity prevention.

Active Screen Time Among U.S. Youth Aged 9–18 Years, 2009

OBJECTIVE This study documented the prevalence of active screen time (i.e., screen time that includes active games, exercise or dance videos, or TV exercise programs) and identified characteristics associated with it among youth 9-18 years of age. SUBJECTS AND METHODS This cross-sectional study was conducted on a convenience sample of 1,165 youth using the 2009 Styles Surveys; data were weighted to approximate the Current Population Survey. We calculated descriptive statistics and conducted multivariable logistic regression to identify characteristics associated with active screen time by estimating adjusted odds ratio (aOR) and 95 percent confidence intervals (CIs). RESULTS The sample comprised 51.4 percent boys, and almost 60 percent were non-Hispanic white. The prevalence of active screen time ≥1 hour/day was 31.2 percent on a typical school day and 41.6 percent on a typical weekend day. Logistic regression revealed youth with physical activity of 3-5 days/week had higher odds of active screen time ≥1 hour/day compared with youth with no physical activity (aOR school day=2.8, 95 percent CI 1.5-5.2; aOR weekend day=2.3, 95 percent CI 1.4-3.9). Certain characteristics (i.e., sex, age group, race/ethnicity, income, and sedentary screen time) were significantly associated with active screen time ≥1 hour/day, but associations were inconsistent for school and weekend days. CONCLUSIONS Three in 10 youth are engaging in at least 1 hour of active screen time on school days, and about 4 in 10 youth are engaging in at least one hour on weekend days. Understanding the use of active screen time and associated characteristics are important for developing interventions addressing screen time and physical activity.