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To describe the quality of food and physical activity (PA) environments by World Bank Income level in jurisdictions from the Children's Healthy Living Program. Baseline cross-sectional community data were analyzed from 11 jurisdictions categorized by World Bank Income levels to describe exposure to different food and PA outlets. The Children's Healthy Living Program was a multilevel, multijurisdictional prevalence study and community intervention trial that reduced child obesity in the US-Affiliated Pacific region. US-Affiliated Pacific region. Food (n = 426) and PA (n = 552) Outlets. Physical activity and food scores that reflect the quality of the outlets that support being physically active and healthy eating options, respectively. Descriptive statistics are presented as means ± SD or percentages. High-income-income level jurisdictions had higher food and PA scores than middle-income level jurisdictions. The US-Affiliated Pacific region has limited quality food and PA outlets in underserved communities at risk for obesity. The findings in this paper can be used to develop tools and design interventions to improve the food and PA environment to increase a healthier, active lifestyle. [ABSTRACT FROM AUTHOR]

Childhood obesity is a public health concern in the United States. Consequences of childhood obesity include metabolic disease and heart, lung, kidney, and other health-related comorbidities. Therefore, the early determination of obesity risk is needed and predicting the trend of a child's body mass index (BMI) at an early age is crucial. Early identification of obesity can lead to early prevention. Multiple methods have been tested and evaluated to assess obesity trends in children. Available growth charts help determine a child's current obesity level but do not predict future obesity risk. The present methods of predicting obesity include regression analysis and machine learning-based classifications and risk factor (threshold)-based categorizations based on specific criteria. All the present techniques, especially current machine learning-based methods, require longitudinal data and information on a large number of variables related to a child's growth (e.g., socioeconomic, family-related factors) in order to predict future obesity-risk. In this paper, we propose three different techniques for three different scenarios to predict childhood obesity based on machine learning approaches and apply them to real data. Our proposed methods predict obesity for children at five years of age using the following three data sets: (1) a single well-child visit, (2) multiple well-child visits under the age of two, and (3) multiple random well-child visits under the age of five. Our models are especially important for situations where only the current patient information is available rather than having multiple data points from regular spaced well-child visits. Our models predict obesity using basic information such as birth BMI, gestational age, BMI measures from well-child visits, and gender. Our models can predict a child's obesity category (normal, overweight, or obese) at five years of age with an accuracy of 89%, 77%, and 89%, for the three application scenarios, respectively. Therefore, our proposed models can assist healthcare professionals by acting as a decision support tool to aid in predicting childhood obesity early in order to reduce obesity-related complications, and in turn, improve healthcare. [ABSTRACT FROM AUTHOR]

According to the Hospital for Special Surgery, approximately 60 million children between the ages of 6 and 18 in the United States participate in organized sports activities every year. This involves approximately 75% of American families, with at least one child participating in an organized sports activity. The stated purposes of participation in organized sports activities are to assist children and teens in building skills, forming friendships, learning the value of teamwork, and possibly obtaining a scholarship to college. There are, however, related challenging issues. According to the Centers for Disease Control , the obesity rate for children and adolescents ages 2–19 living in the United States is 19.3%, affecting approximately 14.4 million children and adolescents. A sedentary lifestyle for children and teenagers contributes to this epidemic, while participation in sports is seen by many as protective. Challenges in participation, including increasing sports-related injuries, a 70% attrition rate by the time a child is 13 years of age, and programs overemphasizing winning are additional problems encountered in pre-teen and teen sports. The effect of pre-teen and teen participation in sports on family relationships is another potential source of stress and anxiety. This is the primary focus of this paper. The family relationships considered are the children, the parents, the couple, and the grandparents. Therapeutic suggestions and intervention considerations are then provided. [ABSTRACT FROM AUTHOR]

Background: To combat the global health crisis of obesity, many interventions have been implemented, including in children and adolescents. This age range is uniquely important because health behavior continues into adulthood, resulting in lifelong health risks or benefits. This narrative reviewaims to provide a cross section of the scientific literature regarding obesity interventions by setting, including schoolbased, daycare-based, home-based, healthcare-based, and digital-based, as well as to highlight gaps in research. Methods: Articles written in English addressing childhood and adolescent obesity interventions were sought online using PubMed and Google Scholar searches. Although some articles were from a global perspective, the majority focused on children in the United States. This search included reviews, individual studies, and other related papers. Results: School-based interventions are accessible to many, but there is limited evidence of long-term benefits. Home-based interventions were the only setting to have compelling evidence of long-term benefits, although there are several barriers to participation. Healthcare-based interventions are often successful when specific strategies and unique advantages of healthcare settings are utilized. Digital interventions have limited success now, but show potential for cost-effective scaling up as technology improves. Conclusion: The clearest gap in research is the lack of long-term studies, especially of school-based and healthcare-based interventions. Thus, it is imperative that investments are made into studies that include follow-up components continuing at least 1-2 years after the intervention. Additionally, home-based interventions have been more successful during early childhood while school-based interventions tend to be more successful during adolescence. [ABSTRACT FROM AUTHOR]

Childhood obesity in the United States is a serious problem that puts children at risk for poor health. Effective state-wide interventions are needed to address childhood obesity risk factors. Embedding evidence-based initiatives into state-level Early Care and Education (ECE) systems has the potential to improve health environments and promote healthy habits for the 12.5 million children attending ECE programs. Go NAPSACC, an online program that was adapted from an earlier paper version of Nutrition and Physical Activity Self-Assessment for Child Care (NAPSACC or NAP SACC), provides an evidence-based approach that aligns with national guidance from Caring for Our Children and the Centers for Disease Control and Prevention. This study describes approaches undertaken across 22 states from May 2017 to May 2022 to implement and integrate Go NAPSACC into state-level systems. This study describes challenges encountered, strategies employed, and lessoned learned while implementing Go NAPSACC state-wide. To date, 22 states have successfully trained 1,324 Go NAPSACC consultants, enrolled 7,152 ECE programs, and aimed to impact 344,750 children in care. By implementing evidence-based programs, such as Go NAPSACC, ECE programs state-wide can make changes and monitor progress on meeting healthy best practice standards, increasing opportunities for all children to have a healthy start. [ABSTRACT FROM AUTHOR]