{'fraction_non_alphanumeric': 0.03004891684136967, 'fraction_numerical': 0.015373864430468204, 'mean_word_length': 5.172413793103448, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Measuring the retail food environment in rural and urban North Carolina counties.

BACKGROUND
Development of accurate and sensitive methods to characterize the food environment is needed. Thus, we examined convergent and criterion validity of 2 retail food environment data sources and then examined differences in predictive validity between 3 ways of measuring the rural and urban food environment.


METHODS
Ten counties were selected in each of 3 North Carolina regions (n = 30). Number of fast-food restaurants and chain supermarkets were calculated using 2 data sources. Convergent validity was percent agreement between the 2 sources. Criterion validity was percent agreement between each source and the most accurate venue count. Predictive validity of food environment measures (Retail Food Environment Index, fast-food restaurants/capita, and supermarkets/capita) was calculated by associations with county-level mean-weighted body mass index (BMI).


RESULTS
Percent agreement for fast-food restaurants ranged from 50% to 100% (mean = 87%) and for supermarkets ranged from 58% to 100% (mean = 89%). The 2 data sources had similar percent agreement with the most accurate count. Retail Food Environment Index was positively associated with BMI, while fast-food restaurants per capita were negatively associated with BMI.


CONCLUSIONS
Our results lend support to studies using both food environment data sources examined.