{'fraction_non_alphanumeric': 0.02711323763955343, 'fraction_numerical': 0.021796916533758637, 'mean_word_length': 5.489655172413793, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
US nationwide assessment of school health policies and practices using state-level data

Objective: After the discontinuation of School Health Policies and Practices Study (SHPPS) in 2016, the US Centers for Disease Control and Prevention (CDC) began exploring innovative ways to gather school health information using existing surveillance systems. School Health Profiles (Profiles) is a school-based system of surveys that monitors school health policies and practices in states and other jurisdictions. The objective of this study was to assess whether prevalence estimates calculated using nationally representative SHPPS as an established benchmark were similar to estimates using aggregated Profiles data. Method: Nationwide 2014 Profiles estimates were calculated from data across all 50 US states and the District of Columbia and compared to national 2014 SHPPS estimates. Fifty-seven questions were identical between the data sources. Equivalence tests were used to determine similarity between data sources. Results: Overall, the median difference between 2014 SHPPS and 2014 Profiles estimate was one percentage point and distribution-free 95% confidence intervals were (−0.8, 3.1). Of the 57 school health policy and practice indicators examined in this study, 38 (66.7%) were found to be equivalent. Of these equivalent indicators, the median percentage point difference between data sources was 0.8 (−0.8, 2.5). A nonparametric sign test showed that none of the medians of the estimate differences examined were significantly different from zero. Conclusion: This study demonstrates the expanded utility of state-level data to meet public health surveillance needs. This study found that aggregated, state-level Profiles data can be used to calculate nationwide prevalence estimates that are reasonably consistent with results from a nationally representative survey.