Evaluation of a Comprehensive School Nutrition Enrichment Intervention (CSNEI) in Rural School Districts

摘要-项目1 在全国范围内，73.6%的成年人超重或肥胖。农村人口和生活在低收入家庭的人 家庭肥胖率高。城市和农村之间肥胖患病率的最大差异 县在美国南部。阿肯色州的农村人口比例位居第六（约41%） 肥胖患病率居第三位（37.4%）。疾病预防控制中心估计，美国2-19岁的儿童中有18.5% 肥胖阿肯色州的高中生肥胖率（22.1%）排名第三， 10-17岁儿童（20.2%）。肥胖导致糖尿病发病率、癌症发病率和 死亡率和心血管疾病发病率和死亡率。本申请寻求 资助首次在农村地区评估学校营养强化综合干预（CSNEI） 学校主要的研究问题是：“与人口统计学上相似的学区相比， 实施CSNEI，CSNEI政策干预是否会改善肥胖预防结果， 农村K-12学生？”我们将进行一项配对的整群随机试验，包括前测和重复的后测。 在6个学区，3个实施CSNEI和3个匹配的比较学区进行测试。评价将 包括6个学区约11，500名学生：约5，750名来自CSNEP学区，约5，750名来自匹配学区 比较学区。本研究将探索人种/种族、性别、年龄、 和经济状况，以了解对肥胖风险最高人群的影响。我们的具体目标是：目标 1.A评估CSNEI对学生相对（考虑年龄和性别）BMI随时间变化的影响。 目的1.B评估CSNEI对食品营养质量的短期和长期影响， 学校餐目标1.C评估CSNEI对学生消费的短期和长期影响 学校提供的食物。目标1.D评估CSNEI对学生的短期和长期影响 皮肤类胡萝卜素水平，作为水果和蔬菜摄入量的指标。目标2：进行执行研究， 记录农村学校实施CSNEI的障碍和促进因素。我们将完成第一个 在农村学校开展国家战略教育倡议的实施研究，这将提供关键信息， 在学区实施类似的干预措施，这将是加快翻译的创新步骤。 实践中的证据。学校营养综合干预措施研究的现有范例 没有适当解决农村儿童，特别是生活在低收入家庭的儿童的需求和潜在障碍。 户这项研究将通过严格评估农村学校的CSNEI来填补关键的证据空白， 有资格享受免费和减价餐的学生比例（>50%）;采用配对集群 随机设计，比较BMI z评分随时间的变化;并将经济状况、年龄（ 月）、性别和种族/民族。

SUMMARY – PROJECT 1 Nationally, 73.6% of adults are overweight or obese. Rural populations and persons living in low-income households have high rates of obesity. The greatest disparities in obesity prevalence between urban and rural counties are in the southern United States. Arkansas has the sixth highest proportion of rural population (~41%) and the third highest obesity prevalence (37.4%). The CDC estimates 18.5% of children age 2-19 in the US are obese. Arkansas has the third highest rate of obesity for high school students (22.1%) and the fifth highest rate for children in ages 10-17 (20.2%). Obesity contributes to increased diabetes incidence, cancer incidence and mortality, and cardiovascular disease incidence and mortality among rural communities. This application seeks funding to evaluate a Comprehensive School Nutrition Enrichment Intervention (CSNEI) for the first time in rural schools. The primary research question is: “Compared with demographically similar school districts that did not implement the CSNEI, does the CSNEI policy intervention yield improved obesity prevention outcomes among rural K-12 students?” We will conduct a matched-pairs cluster randomized trial with pre-test and repeated post- tests in 6 school districts, 3 implementing CSNEI and 3 matched comparison school districts. The evaluation will include ~11,500 students in 6 school districts: ~5,750 from CSNEP school districts and ~5,750 from matched comparison school districts. The study will explore heterogeneity of treatment effects for race/ethnicity, sex, age, and economic status to understand effects on populations most at risk for obesity. Our specific aims are: Aim 1.A Evaluate the effects of a CSNEI on students' relative (accounting for age and sex) BMI change over time. Aim 1.B Evaluate the short-term and long-term effects of a CSNEI on the nutritional quality of food served in school meals. Aim 1.C Evaluate the short-term and long-term effects of a CSNEI on students' consumption of food served in school meals. Aim 1.D Evaluate the short-term and long-term effects of a CSNEI on students' skin carotenoid levels, as an indicator of fruit and vegetable intake. Aim 2 Conduct an implementation study to document barriers and facilitators of CSNEI implementation in rural schools. We will complete the first implementation study of a CSNEI in rural schools, which will provide critical information to ensure successful implementation of similar interventions in school districts and will be an innovative step to accelerate translation of evidence into broad practice. Existing paradigms for the study of comprehensive school nutrition interventions do not appropriately address needs and potential barriers of rural children, particularly those living in low-income households. This study will fill critical gaps in evidence by rigorously evaluating a CSNEI in rural schools with high proportions of students eligible for free and reduced price meals (>50%); employing a matched-pairs cluster randomized design to compare changes in BMI z-scores over time; and incorporating economic status, age (in months), sex, and race/ethnicity in the analyses.