An outbreak of Salmonella Enteritidis food poisoning following consumption of chicken shawarma: A brief epidemiological investigation

Background: Shawarma, a popular meat-based fast food could be a source of foodborne outbreak due to non-typhoidal Salmonella (NTS). A clustering of acute gastrointestinal (GI) illness following intake of chicken shawarma occurred primarily among the staff and students of a tertiary care hospital in southern India. Methods: A case-control study was conducted among 348 undergraduate medical students (33 cases, 315 controls). Data was collected using direct interviews and a simple online questionnaire. Epidemiological associations of GI illness were evaluated at three levels of exposure namely-eating food from any restaurant, eating food from the implicated food outlet, eating chicken shawarma from the implicated outlet. Results: Of 33 cases, 26 had consumed food from a particular food outlet, 4 from other outlets, and 3 did not report eating out. Consumption of food from the suspected food outlet was significantly associated with GI illness (odds ratio 121.8 [95% CI 28.41 to 522.66]; P<0.001); all the 26 cases who had eaten from the particular outlet had eaten chicken shawarma. By comparison, only one of the 315 controls had eaten this dish. Of the 27 persons (cases as well as controls) who had consumed chicken shawarma from the outlet, 26 were ill. Culture of stool samples from 10 affected individuals and implicated food item yielded Salmonella Enteritidis. Conclusions: Meat-based shawarma is a potential source of NTS infection. Food safety authorities should enforce guidelines for safe preparation and sale of shawarmas and similar products.

An outbreak of Salmonella Enteritidis food poisoning following consumption of chicken shawarma: A brief epidemiological investigation

Background: Shawarma, a popular meat-based fast food could be a source of foodborne outbreak due to non-typhoidal Salmonella (NTS). A clustering of acute gastrointestinal (GI) illness following intake of chicken shawarma occurred primarily among the staff and students of a tertiary care hospital in southern India. Methods: A case-control study was conducted among 348 undergraduate medical students (33 cases, 315 controls). Data was collected using direct interviews and a simple online questionnaire. Epidemiological associations of GI illness were evaluated at three levels of exposure namely-eating food from any restaurant, eating food from the implicated food outlet, eating chicken shawarma from the implicated outlet. Results: Of 33 cases, 26 had consumed food from a particular food outlet, 4 from other outlets, and 3 did not report eating out. Consumption of food from the suspected food outlet was significantly associated with GI illness (odds ratio 121.8 [95% CI 28.41 to 522.66]; P<0.001); all the 26 cases who had eaten from the particular outlet had eaten chicken shawarma. By comparison, only one of the 315 controls had eaten this dish. Of the 27 persons (cases as well as controls) who had consumed chicken shawarma from the outlet, 26 were ill. Culture of stool samples from 10 affected individuals and implicated food item yielded Salmonella Enteritidis. Conclusions: Meat-based shawarma is a potential source of NTS infection. Food safety authorities should enforce guidelines for safe preparation and sale of shawarmas and similar products.

Predicting Food Safety Compliance for Informed Food Outlet Inspections: A Machine Learning Approach

Consumer food environments have transformed dramatically in the last decade. Food outlet prevalence has increased, and people are eating food outside the home more than ever before. Despite these developments, national spending on food control has reduced. The National Audit Office report that only 14% of local authorities are up to date with food business inspections, exposing consumers to unknown levels of risk. Given the scarcity of local authority resources, this paper presents a data-driven approach to predict compliance for newly opened businesses and those awaiting repeat inspections. This work capitalizes on the theory that food outlet compliance is a function of its geographic context, namely the characteristics of the neighborhood within which it sits. We explore the utility of three machine learning approaches to predict non-compliant food outlets in England and Wales using openly accessible socio-demographic, business type, and urbanness features at the output area level. We find that the synthetic minority oversampling technique alongside a random forest algorithm with a 1:1 sampling strategy provides the best predictive power. Our final model retrieves and identifies 84% of total non-compliant outlets in a test set of 92,595 (sensitivity = 0.843, specificity = 0.745, precision = 0.274). The originality of this work lies in its unique and methodological approach which combines the use of machine learning with fine-grained neighborhood data to make robust predictions of compliance.

A continuous indicator of food environment nutritional quality

Food environments can profoundly impact diet and related diseases. Effective, robust measures of food environment nutritional quality are required by researchers and policymakers investigating their effects on individual dietary behavior and designing targeted public health interventions. The most commonly used indicators of food environment nutritional quality are limited to measuring the binary presence or absence of entire categories of food outlet type, such as 'fast-food' outlets, which can range from burger joints to salad chains. This work introduces a summarizing indicator of restaurant nutritional quality that exists along a continuum, and which can be applied at scale to make distinctions between diverse restaurants within and across categories of food outlets. Verified nutrient data for a set of over 500 chain restaurants is used as ground-truth data to validate the approach. We illustrate the use of the validated indicator to characterize food environments at the scale of an entire jurisdiction, demonstrating how making distinctions between different shades of nutritiousness can help to uncover hidden patterns of disparities in access to high nutritional quality food.

Associations between online food outlet access and online food delivery service use amongst adults in the UK: a cross-sectional analysis of linked data

Background Online food delivery services facilitate ‘online’ access to food outlets that typically sell lenergy-dense nutrient-poor food. Greater online food outlet access might be related to the use of this purchasing format and living with excess bodyweight, however, this is not known. We aimed to investigate the association between aspects of online food outlet access and online food delivery service use, and differences according to customer sociodemographic characteristics, as well as the association between the number of food outlets accessible online and bodyweight. Methods In 2019, we used an automated data collection method to collect data on all food outlets in the UK registered with the leading online food delivery service Just Eat (n = 33,204). We linked this with contemporaneous data on food purchasing, bodyweight, and sociodemographic information collected through the International Food Policy Study (analytic sample n = 3067). We used adjusted binomial logistic, linear, and multinomial logistic regression models to examine associations. Results Adults in the UK had online access to a median of 85 food outlets (IQR: 34–181) and 85 unique types of cuisine (IQR: 64–108), and 15.1% reported online food delivery service use in the previous week. Those with the greatest number of accessible food outlets (quarter four, 182–879) had 71% greater odds of online food delivery service use (OR: 1.71; 95% CI: 1.09, 2.68) compared to those with the least (quarter one, 0–34). This pattern was evident amongst adults with a university degree (OR: 2.11; 95% CI: 1.15, 3.85), adults aged between 18 and 29 years (OR: 3.27, 95% CI: 1.59, 6.72), those living with children (OR: 1.94; 95% CI: 1.01; 3.75), and females at each level of increased exposure. We found no association between the number of unique types of cuisine accessible online and online food delivery service use, or between the number of food outlets accessible online and bodyweight. Conclusions The number of food outlets accessible online is positively associated with online food delivery service use. Adults with the highest education, younger adults, those living with children, and females, were particularly susceptible to the greatest online food outlet access. Further research is required to investigate the possible health implications of online food delivery service use.

Investigating mobility-based fast food outlet visits as indicators of dietary intake and diet-related disease

IMPORTANCE: Excessive consumption of fast food (FF) is associated with chronic disease. Population-level research on FF outlet visits is now possible with mobility data, however its usefulness as an indicator of FF intake and diet-related disease must be established. OBJECTIVE: Investigate whether FF outlet visits from mobility data are indicators of self-reported FF intake, obesity, and diabetes, and compared with self-reported intake, equivalent or better indicators of obesity and diabetes. DESIGN, SETTING, AND PARTICIPANTS: A secondary analysis of data from a representative sample of 8,036 adult residents of Los Angeles County (LAC) from the 2011 Los Angeles County Health Survey (LACHS), and mobility data representing all geolocations between October 2016 - March 2017 of 243,644 anonymous and opted-in smartphone users in LAC. MAIN OUTCOMES AND MEASURES: Main outcomes were self-reported FF intake frequency (never, infrequent, moderate, frequent), obesity, and diabetes from LACHS. FF outlet visits were computed as the temporal frequency of FF visits (FF visits/time) and the ratio of visits to FF over all food outlets (FF visits/food), summarized over smartphone users in a neighborhood, scaled from 0-10, and linked to LACHS respondents by census tract. RESULTS: The analytic sample included 5,447 LACHS respondents and 234,995 smartphone users with 14,498,850 visits to food outlets. FF outlet visits were significantly associated with self-reported FF intake (reference: never) for both FF visits/time (infrequent: odds ratio [OR], 1.13; 95% CI, 1.06-1.20; frequent: OR, 1.35; 95% CI, 1.28-1.42) and FF visits/food (infrequent: OR, 1.12; 95% CI, 1.06-1.17; frequent: OR, 1.28; 95% CI, 1.22-1.33). FF outlet visits were significantly associated with obesity (FF visits/time: adjusted OR [AOR], 1.16; 95% CI, 1.12-1.21; FF visits/food: AOR, 1.13; 95% CI, 1.10-1.17) and diabetes (FF visits/time: AOR, 1.15; 95% CI, 1.09-1.21; FF visits/food: AOR, 1.11; 95% CI, 1.07-1.16), adjusted for sociodemographic factors. Models of the association between FF outlet visits and obesity or diabetes had better fits than between self-reported FF intake and obesity or diabetes. CONCLUSIONS AND RELEVANCE: This study illustrates that population-scale mobility data provide useful, passively-collected indicators of FF intake and diet-related disease within large, diverse urban populations that may be better than self-report intake. KEY POINTS QUESTION: Do visits to fast food outlets observed in mobility data provide meaningful measures of fast food intake, and when compared with self-reported intake, equivalent or better indicators of diet-related disease? FINDINGS: In this cross-sectional Los Angeles County study from a survey of 8,036 adults and mobility data from 243,644 smartphone users with 14.5 million food outlet visits, neighborhood-level features representing visits to fast food outlets were significantly associated with self-reported fast food intake, significantly associated with obesity and diabetes, and were a better predictor of these diseases than self-reported fast food intake. MEANING: Measures of food behaviors observed in population-scale mobility data can provide meaningful indicators of food intake and diet-related diseases, and could complement existing dietary surveillance methods.

Neighborhood food typologies, fast food outlet visitation and snack food purchasing among adolescents in Melbourne, Australia

Objective: Despite the increased attention on neighborhood food environments and dietary behaviors, studies focusing on adolescents are limited. This study aims to characterize typologies of food environments surrounding adolescents and their associations with fast food outlet visitation and snack food purchasing to/from school. Design: The number of food outlets (supermarket; green grocers; butcher/seafood/deli; bakeries; convenience stores; fast food/takeaways; café and restaurants) within a 1km buffer from home were determined using a Geographic Information System. Adolescents self-reported frequency of fast food outlet visitation and snack food purchasing to/from school. Latent Profile Analysis was conducted to identify typologies of the food environment. Cross-sectional multilevel logistic regression analyses were conducted to examine the relationships between food typologies, fast food outlet visitations and snack food purchasing to/from school. Setting: Melbourne, Australia Participants: 410 adolescents (mean age= 15.5 (SD=1.5) years) Results: Four distinct typologies of food outlets were identified: 1) limited variety/low number; 2) some variety/low number; 3) high variety/medium number; 4) high variety/high number. Adolescents living in Typologies 1 and 2 had three times higher odds of visiting fast food outlets ≥1 per week (Typology 1: OR= 3.71, 95%CI 1.23, 11.19; Typology 2: OR= 3.65, 95% CI 1.21, 10.99) than those living in Typology 4. No evidence of association was found between typologies of the food environments and snack food purchasing behavior to/from school among adolescents. Conclusion: Local government could emphasize an overall balance of food outlets when designing neighborhoods to reduce propensity for fast food outlet visitation among adolescents.