Introduction
Children consume much of their daily energy intake at school. School district policies, state laws, and national policies, such as revisions to the US Department of Agriculture’s school meals standards, may affect the types of foods and beverages offered in school lunches over time.
Methods
This study evaluated changes and disparities in school lunch characteristics from 2006–2007 to 2013–2014. Data were obtained from annual cross-sectional surveys at 4,630 public elementary schools participating in the National School Lunch Program. Multivariate logistic regressions were conducted to examine lunch characteristics.
Results
The percentage of schools regularly offering healthful items such as vegetables (other than potatoes), fresh fruit, salad bars, whole grains, and more healthful pizzas increased significantly from 2006–2007 to 2013–2014, and the percentage of schools offering less healthful items such as fried potatoes, regular pizza, and high-fat milks decreased significantly. Nevertheless, disparities were evident in 2013–2014. Schools in the West were significantly more likely to offer salad bars than were schools in the Northeast, Midwest, or South (adjusted prevalence: West, 66.3%; Northeast, 22.3%; Midwest, 20.8%; South, 18.3%). Majority-black or majority-Latino schools were significantly less likely to offer fresh fruit than were predominantly white schools (adjusted prevalence: majority black, 61.3%; majority Latino, 73.0%; predominantly white, 87.8%). Schools with low socioeconomic status were significantly less likely to offer salads regularly than were schools with middle or high socioeconomic status (adjusted prevalence: low, 38.5%; middle, 47.4%; high, 59.3%).
Conclusion
Much progress has been made in improving the quality of school lunches in US public elementary schools, but additional opportunities for improvement remain.
The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five ew Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by RWJF's New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity.
Effective interventions for addressing childhood obesity require community specific information on who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community.
Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy Kids and the five communities to address these information needs. The main components of the study include:
• A household survey of 1700 families with 3 -18 year old children
• De-identified heights and weights data from public school districts
• Assessment of the food and physical activity environments using objective data
Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.
The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland.
These five communities are being supported by RWJF's New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity.
Effective interventions for addressing childhood obesity require community-specific information on who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community.
Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy I<ids and the five communities to address these information needs. The main components of the study include:
• A household survey of 1700 families with 3 -18 year old children
• De-identified heights and weights data from public school districts
• Assessment of the food and physical activity environments using objective data
Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.
The New Jersey Childhood Obesity Study, funded by the Robert Wood Johnson Foundation, aims to provide vital information for planning, implementing and evaluating interventions aimed at preventing childhood obesity in five New Jersey municipalities: Camden, Newark, New Brunswick, Trenton, and Vineland. These five communities are being supported by RWJF's New Jersey Partnership for Healthy Kids program to plan and implement policy and environmental change strategies to prevent childhood obesity.
Effective interventions for addressing childhood obesity require community specific information on who is most at risk and on contributing factors that can be addressed through tailored interventions that meet the needs of the community.
Using a comprehensive research study, the Center for State Health Policy at Rutgers University is working collaboratively with the State Program Office for New Jersey Partnership for Healthy Kids and the five communities to address these information needs. The main components of the study include:
• A household survey of 1700 families with 3 -18 year old children
• De-identified heights and weights data from public school districts
• Assessment of the food and physical activity environments using objective data
Data books and maps based on the results of the study are being shared with the community coalitions in the five communities to help them plan their interventions.
The epidemic of overweight and obesity and its multiple causes have captured the attention of researchers, program administrators, politicians, and the public alike. Recently, many stakeholder groups have started investigating the role that food and nutrition assistance programs play in the etiology of the problem and in identifying possible solutions. As a result, policy changes have been recommended and implemented for programs such as the National School Lunch Program (NSLP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) to improve the nutritional quality of foods they offer to their participants. The Supplemental Nutrition Assistance Program (SNAP) is also attracting attention as a potential vehicle to reduce the burden of obesity among its users. Because of the tough economic and political climate in which all federal programs currently operate, the need for making nutrition assistance programs more efficient and effective in addressing health and nutrition related problems affecting the country has never been greater.
This document proposes a set of strategies to improve the effectiveness and efficiency of SNAP. These strategies are based on a review of research literature, recommendations from expert groups, and the experiences of other communities and states. We include information that pertains to potential stakeholder arguments for and against each strategy, as well as the political feasibility, financial impact, and logistical requirements for implementation. We drew candidate strategies from the range of options that have been tested through research and from policies that have been implemented around the country. The order of strategies in this document is based on overall strength of supportive research, as well as political and implementation feasibility. The four proposed strategies are improving access to healthy foods to provide better choices, incentivizing the purchase of healthy foods, restricting access to unhealthy foods, and maximizing education to more effectively reach a larger population of SNAP participants.
Objectives: Conflicting findings on associations between food and physical activity (PA) environments and children's weight status demand attention in order to inform effective interventions. We assess relationships between the food and PA environments in inner-city neighborhoods and children's weight status and address sources of conflicting results of prior research.
Methods: Weight status of children ages 3-18 was assessed using parent-measured heights and weights. Data were collected from 702 children living in four low-income cities in New Jersey between 2009 and 2010. Proximity of a child's residence to a variety of food and PA outlets was measured in multiple ways using geo-coded data. Multivariate analyses assessed the association between measures of proximity and weight status.
Results: Significant associations were observed between children's weight status and proximity to convenience stores in the 1/4 mile radius (OR = 1.9) and with presence of a large park in the 1/2 mile radius (OR = 0.41). No associations were observed for other types of food and PA outlets.
Conclusions: Specific aspects of the food and PA environments are predictors of overweight and obese status among children, but the relationships and their detection are dependent upon aspects of the geospatial landscape of each community.
Background: The Nike + Fuelband is a commercially available, wrist-worn accelerometer used to track physical activity energy expenditure (PAEE) during exercise. However, validation studies assessing the accuracy of this device for estimating PAEE are lacking. Therefore, this study examined the validity and reliability of the Nike + Fuelband for estimating PAEE during physical activity in young adults. Secondarily, we compared PAEE estimation of the Nike + Fuelband with the previously validated SenseWear Armband (SWA).
Methods: Twenty-four participants (n = 24) completed two, 60-min semi-structured routines consisting of sedentary/light-intensity, moderate-intensity, and vigorous-intensity physical activity. Participants wore a Nike + Fuelband and SWA, while oxygen uptake was measured continuously with an Oxycon Mobile (OM) metabolic measurement system (criterion).
Results: The Nike + Fuelband (ICC = 0.77) and SWA (ICC = 0.61) both demonstrated moderate to good validity. PAEE estimates provided by the Nike + Fuelband (246 ± 67 kcal) and SWA (238 ± 57 kcal) were not statistically different than OM (243 ± 67 kcal). Both devices also displayed similar mean absolute percent errors for PAEE estimates (Nike + Fuelband = 16 ± 13 %; SWA = 18 ± 18 %). Test-retest reliability for PAEE indicated good stability for Nike + Fuelband (ICC = 0.96) and SWA (ICC = 0.90).
Conclusion: The Nike + Fuelband provided valid and reliable estimates of PAEE, that are similar to the previously validated SWA, during a routine that included approximately equal amounts of sedentary/light-, moderate- and vigorous-intensity physical activity.
Background: Aspects of the food environment such as the availability of different types of food stores have recently emerged as key modifiable factors that may contribute to the increased prevalence of obesity. Given that many of these studies have derived their results based on secondary datasets and the relationship of food stores with individual weight outcomes has been reported to vary by store type, it is important to understand the extent to which often-used secondary data correctly classify food stores. We evaluated the classification bias of food stores in Dun & Bradstreet (D&B) and InfoUSA commercial business lists.
Methods: We performed a full census in 274 randomly selected census tracts in the Chicago metropolitan area and collected detailed store attributes inside stores for classification. Store attributes were compared by classification match status and store type. Systematic classification bias by census tract characteristics was assessed in multivariate regression.
Results: D&B had a higher classification match rate than InfoUSA for supermarkets and grocery stores, while InfoUSA was higher for convenience stores. Both lists were more likely to correctly classify large supermarkets, grocery stores, and convenience stores with more cash registers and different types of service counters (supermarkets and grocery stores only). The likelihood of a correct classification match for supermarkets and grocery stores did not vary systemically by tract characteristics whereas convenience stores were more likely to be misclassified in predominately Black tracts.
Conclusion: Researches can rely on classification of food stores in commercial datasets for supermarkets and grocery stores whereas classifications for convenience and specialty food stores are subject to some systematic bias by neighborhood racial/ethnic composition.