Sodium content of menu items in New York City chain restaurants following enforcement of the sodium warning icon rule, 2015-2017.

In 2016, New York City (NYC) began enforcing a sodium warning regulation at chain restaurants, requiring placement of an icon next to any menu item containing ≥2,300 mg sodium. As menu labeling may improve menu nutritional composition, we investigated whether sodium content of menu items changed following enforcement of the sodium warning icon. All menu offerings at 10 quick-service (QSR) and 3 full-service (FSR) chain restaurants were photographed in 2015 (baseline) and 2017 (follow-up) and matched to nutritional information from restaurant websites; items were categorized as being available at both baseline and follow-up, or at only one timepoint. Linear and logistic regression models, respectively, assessed changes in calculated mean sodium-per-serving per menu item and the odds of an item containing ≥2,300 mg sodium. At baseline, mean per-serving sodium content was 2,160 mg at FSR and 1,070 mg at QSR, and 40.6% of FSR items and 7.2% of QSR items contained ≥2,300 mg sodium per serving. Sodium content did not differ when comparing all items offered at follow-up to all offered at baseline (21 mg, 95% CI: -60,101), or when comparing new versus discontinued items (17 mg, 95% CI: -154, 187). At follow-up, there was no change in the overall likelihood of items requiring a warning icon (OR = 1.32, 95% CI: 0.97,1.79), or when comparing new versus discontinued items (OR = 2.08, 95% CI: 1.02,4.24) (p = 0.04, not significant following Bonferroni correction for multiple analyses). Our findings that the sodium content of menu items did not change following the sodium warning icon regulation underscore difficulties in reducing sodium levels in restaurants; however, our results may be limited by follow-up data collection occurring less than one year post-enforcement. It may take additional time and similar action from other jurisdictions for restaurants to reduce the sodium content of menu items.

Changes in consumer purchasing patterns at New York City chain restaurants following adoption of the sodium warning icon rule, 2015-2017.

In 2016, New York City (NYC) began enforcing a sodium warning regulation at chain restaurants, requiring placement of an icon next to any menu item containing ≥2,300 mg sodium. As shifts in consumer purchases are a potential outcome of menu labeling, we investigated whether high-sodium purchases from NYC chains changed following policy implementation. Using receipts for verification, consumer purchases were assessed at 2 full-service (FSR) and 2 quick-service (QSR) chain restaurants in NYC and Yonkers, NY, which did not implement sodium menu labeling, in 2015 and 2017. Primary outcomes included the proportion of respondents purchasing high-sodium item(s) (containing ≥2,300 mg sodium) and mean sodium content of purchases; changes were assessed by difference-in-difference regression models, adjusted for demographic and location co-variates. At both FSR and QSR, there was not a significant change in the proportion of NYC respondents purchasing 1 or more high-sodium items, relative to Yonkers (FSR difference-in-difference: -4.6%, p = 0.364; QSR difference-in-difference: -8.9%, p = 0.196). Among NYC FSR respondents, mean sodium content of purchases significantly declined compared to Yonkers (difference-in-difference: -524 mg, p = 0.012); no changes in mean sodium were observed among QSR participants (difference-in-difference: 258 mg, p = 0.185). Although there was a reduction in mean sodium content of purchases among NYC FSR patrons following sodium warning icon implementation, the mechanism behind the relatively larger NYC decline is unknown.

Beverage Availability and Price: Variations by Neighborhood Poverty Level in New York City.

Objective: To describe the variability in the availability and price of sugary drinks, low-calorie drinks, and water/seltzer across high- and low-poverty census tracts in the five boroughs of New York City (NYC). Design: Cross-sectional study. Our primary analysis compared the overall sample of beverages. Secondary analyses included tests for differences in the availability of beverage categories by neighborhood poverty level. Setting: We collected data from 106 stores (31 supermarkets, 29 convenience stores, 29 pharmacies, 9 Targets, and 8 Dollar Trees) in NYC. Fifty-four stores were located in high-poverty census tracts and 52 were located in low-poverty census tracts. Results: The mean Price per 0.03-liter of sugary drinks across the sample was $0.08, which was significantly higher than the price of low-calorie drinks ($0.07, p=0.01) but not different from water/seltzer ($0.08, p=0.65). Sugary drinks and water/seltzer were available in 91% of retailers, and low-calorie drinks were available in 87% of retailers. There was no statistical difference in availability of sugary drinks compared with low-calorie drinks or water/seltzer overall or within high- or low-poverty census tracts. Analyzed by store type, the mean price per ounce of sugary drinks differed significantly from water/seltzer at convenience stores, pharmacies, and Target stores (bodegas: $0.08 vs. $0.09, p=0.03; pharmacies: $0.11 vs. $0.08, p=0.02; Target stores: $0.07 vs. $0.09, p=0.01). Conclusions: Sugary drinks were available in most food retail settings in NYC, with little variation by census tract poverty level. Interventions that raise the price of sugary drinks to make healthier alternatives, such as water, the more affordable option should be considered.

Assessing changes in the food retail environment during the COVID-19 pandemic: opportunities, challenges, and lessons learned.

BACKGROUND: COVID-19 mitigation strategies have had an untold effect on food retail stores and restaurants. Early evidence from New York City (NYC) indicated that these strategies, among decreased travel from China and increased fears of viral transmission and xenophobia, were leading to mass closures of businesses in Manhattan's Chinatown. The constantly evolving COVID -19 crisis has caused research design and methodology to fundamentally shift, requiring adaptable strategies to address emerging and existing public health problems such as food security that may result from closures of food outlets. OBJECTIVE: We describe innovative approaches used to evaluate changes to the food retail environment amidst the constraints of the pandemic in an urban center heavily burdened by COVID-19. Included are challenges faced, lessons learned and future opportunities. METHODS: First, we identified six diverse neighborhoods in NYC: two lower-resourced, two higher-resourced, and two Chinese ethnic enclaves. We then developed a census of food outlets in these six neighborhoods using state and local licensing databases. To ascertain the status (open vs. closed) of outlets pre-pandemic, we employed a manual web-scraping technique. We used a similar method to determine the status of outlets during the pandemic. Two independent online sources were required to confirm the status of outlets. If two sources could not confirm the status, we conducted phone call checks and/or in-person visits. RESULTS: The final baseline database included 2585 food outlets across six neighborhoods. Ascertaining the status of food outlets was more difficult in lower-resourced neighborhoods and Chinese ethnic enclaves compared to higher-resourced areas. Higher-resourced neighborhoods required fewer phone call and in-person checks for both restaurants and food retailers than other neighborhoods. CONCLUSIONS: Our multi-step data collection approach maximized safety and efficiency while minimizing cost and resources. Challenges in remote data collection varied by neighborhood and may reflect the different resources or social capital of the communities; understanding neighborhood-specific constraints prior to data collection may streamline the process.

COVID-19 Leads to Dramatic Changes in the Food Retail Environment in New York City: May-July 2020.

A systematic assessment of the effect of COVID-19 on the food retail environment-an important determinant of health-has not been conducted. Our objective was to assess the impact of COVID-19 on closures of restaurants, food retail stores, and fresh produce vendors in New York City (NYC). We conducted a cross-sectional study following the peak of COVID-19 in six neighborhoods in NYC. Two Chinese ethnic neighborhoods and four higher/lower resourced comparison neighborhoods were selected a priori based on 14 sociodemographic indicators. The primary outcome was indefinite/temporary closures or absence of food businesses. Of 2720 food businesses identified, produce vendors and restaurants were more likely to close than food retail stores. A higher proportion of food businesses closed in Chinese ethnic neighborhoods vs. comparison neighborhoods. COVID-19 impacted food businesses in six NYC neighborhoods examined in this period, with the greatest effect observed for Chinese ethnic neighborhoods.

Evaluating Closures of Fresh Fruit and Vegetable Vendors During the COVID-19 Pandemic: Methodology and Preliminary Results Using Omnidirectional Street View Imagery.

BACKGROUND: The COVID-19 pandemic has significantly disrupted the food retail environment. However, its impact on fresh fruit and vegetable vendors remains unclear; these are often smaller, more community centered, and may lack the financial infrastructure to withstand supply and demand changes induced by such crises. OBJECTIVE: This study documents the methodology used to assess fresh fruit and vegetable vendor closures in New York City (NYC) following the start of the COVID-19 pandemic by using Google Street View, the new Apple Look Around database, and in-person checks. METHODS: In total, 6 NYC neighborhoods (in Manhattan and Brooklyn) were selected for analysis; these included two socioeconomically advantaged neighborhoods (Upper East Side, Park Slope), two socioeconomically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, Google Street View was used to virtually walk down each street and identify vendors (stores, storefronts, street vendors, or wholesalers) that were open and active in 2019 (ie, both produce and vendor personnel were present at a location). Past vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was geotagged as a Google Maps pinpoint that research assistants then physically visited. Using the "notes" feature of Google Maps as a data collection tool, notes were made on which of three categories best described each vendor: (1) open, (2) open with a more limited setup (eg, certain sections of the vendor unit that were open and active in 2019 were missing or closed during in-person checks), or (3) closed/absent. RESULTS: Of the 135 open vendors identified in 2019 imagery data, 35% (n=47) were absent/closed and 10% (n=13) were open with more limited setups following the beginning of the COVID-19 pandemic. When comparing boroughs, 35% (28/80) of vendors in Manhattan were absent/closed, as were 35% (19/55) of vendors in Brooklyn. Although Google Street View was able to provide 2019 street view imagery data for most neighborhoods, Apple Look Around was required for 2019 imagery data for some areas of Park Slope. Past surveillance data helped to identify 3 additional established vendors in Chinatown that had been missed in street view imagery. The Google Maps "notes" feature was used by multiple research assistants simultaneously to rapidly collect observational data on mobile devices. CONCLUSIONS: The methodology employed enabled the identification of closures in the fresh fruit and vegetable retail environment and can be used to assess closures in other contexts. The use of past baseline surveillance data to aid vendor identification was valuable for identifying vendors that may have been absent or visually obstructed in the street view imagery data. Data collection using Google Maps likewise has the potential to enhance the efficiency of fieldwork in future studies.

Examining Trends in Beverage Sales in New York City During Comprehensive Efforts to Reduce Sugary Drink Consumption, 2010-2015.

Since 2006, New York City (NYC) has attempted to reduce sugary drink consumption through several population-based initiatives, media campaigns and policy proposals. We estimated trends in the relative market share of sugary drinks and other beverage categories in NYC, using over 5 years of weekly, point-of-sale data from a retailer sample. We used an interrupted time series approach to assess whether changes in NYC beverage purchasing patterns occurred following the announcement of a proposed portion cap rule for consumer purchases of sugary drinks. Overall, market share of sugary drinks declined in NYC between 2010 and 2015. While the proportion of beverage volume sold that was sugary drinks was stable prior to the May 2012 portion cap rule announcement, decreases of 1.25% per year were observed in the period following the announcement compared to the period before (95% confidence interval (CI) - 1.60, - 0.90). Water/seltzer market share was increasing prior to the announcement and increased by an additional 1.03% per year in the post-announcement period (95% CI 0.48, 1.57). City-led efforts to increase public awareness about sugary drink-associated health risks in NYC may have led to reductions in consumer purchases of these beverages. Though never implemented, the portion cap proposal and accompanying media coverage may have contributed to decreases in sugary drink sales.

Ubiquity of Sugary Drinks and Processed Food Throughout Food and Non-Food Retail Settings in NYC.

Sugary drinks and processed foods are associated with negative health outcomes in adults, including weight gain, and their consumption should be limited. However, they may be difficult to avoid if they are ubiquitously available in the retail environment. This study aimed to quantify the availability of such products for sale throughout New York City (NYC) at both food and non-food retailers. In 2018, ten one-mile retail-dense NYC street segments were selected for the sample. Data collectors canvassed each segment and visited all retailers, recording the type (food/non-food) and presence of processed food and beverages for sale. Descriptive statistics were analyzed for availability of products sold in retailers overall and by retailer type. In total, 491 retailers were identified (191 food, 300 non-food). Sugary drinks were available at 83% of food retailers and 19% of non-food retailers, while processed foods were available at 61% of food retailers and 16% of non-food retailers. Eighty-five percent of food retailers and 21% of non-food retailers sold sugary drinks and/or processed foods. This study supports and builds on results of previous research examining the availability of food and beverages in the retail environment. Sugary drinks and processed foods are ubiquitous at food and non-food retailers, providing pervasive cues to consume energy-dense, nutrient-poor products. Restrictions on where such products can be sold merit consideration.

Sodium, calorie, and sugary drink purchasing patterns in chain restaurants: Findings from NYC.

To understand how consumer purchases in chain restaurants relate to nutrients of public health concern, sodium, calories and sugary drinks purchased for personal consumption were assessed through a customer intercept receipt study at a sample of New York City quick- and full-service chain restaurants (QSR and FSR) in 2015. The percentages of respondents purchasing ≥2,300 mg sodium, ≥2,000 calories, and a sugary drink, respectively, were 14%, 3% and 32% at QSR, and 56%, 23%, and 22% at FSR. Sodium content of purchases averaged 1,260 mg at QSR and 2,897 mg at FSR and calories averaged 770 at QSR and 1,456 at FSR. 71% of QSR sugary drink purchases contained at least 200 calories. Purchasing patterns that are exceptionally high in sodium and calories, and that include sugary drinks, are common in chain restaurants. Because restaurant-sourced foods are a cornerstone of the American diet, fostering conditions that support healthful purchases is essential to reduce preventable disease and advance health.