Inspection Frequency, Sociodemographic Factors, and Food Safety Violations in Chain and Nonchain Restaurants, Philadelphia, Pennsylvania, 2013-2014

2013-2014年宾夕法尼亚州费城连锁餐厅和非连锁餐厅的检查频率、社会人口因素和食品安全违规情况

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Abstract

OBJECTIVES: We explored how restaurant inspection frequency and restaurant neighborhood sociodemographic characteristics are related to food safety inspection outcomes in chain and nonchain restaurants to better understand external factors that may influence inspection outcomes. METHODS: We categorized the results of restaurant inspections in Philadelphia, Pennsylvania, in 2013 and 2014 by restaurant type (chain or nonchain), inspection frequency (1, 2, or ≥3 per 2-year study period), and violation type (total number of violations, foodborne-illness risk factor violation, or good retail practice violation). We collected 2013 US Census block group sociodemographic data for each restaurant neighborhood. We used nested mixed-effects regression analyses to determine the association between restaurant inspection frequency and inspection violations, as well as between inspection violations and restaurant neighborhood sociodemographic variables, stratified by restaurant type. RESULTS: Compared with nonchain restaurants, chain restaurants had significantly fewer total violations per inspection (mean [SD]: 6.5 [4.6] vs 9.6 [6.8] violations, P < .001). For nonchain restaurants, an increase from 1 to 2 inspections resulted in 0.8 ( P < .001) fewer mean violations per inspection, and an increase from 1 to ≥3 inspections resulted in 1.6 ( P < .001) fewer mean violations; this association was not seen in chain restaurants. For nonchain restaurants, a higher proportion of black residents in a restaurant neighborhood was associated with 0.6 ( P < .001) fewer mean foodborne-illness risk factor violations but 1.0 ( P < .001) more mean good retail practice violations per inspection. CONCLUSIONS: A risk-based stratified approach to restaurant food safety inspection frequency, based on whether or not restaurants are part of chains, could reduce the frequency of violations, particularly in restaurants with the most violations.

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