Cathy Nonas

Purchasing behavior and calorie information at fast-food chains in New York City, 2007.

We surveyed 7318 customers from 275 randomly selected restaurants of 11 fast food chains. Participants purchased a mean of 827 calories, with 34% purchasing 1000 calories or more. Unlike other chains, Subway posted calorie information at point of purchase and its patrons more often reported seeing calorie information than patrons of other chains (32% vs 4%; P<.001); Subway patrons who saw calorie information purchased 52 fewer calories than did other Subway patrons (P<.01). Fast-food chains should display calorie information prominently at point of purchase, where it can be seen and used to inform purchases.

Changes in energy content of lunchtime purchases from fast food restaurants after introduction of calorie labelling: cross sectional customer surveys

Objective To assess the impact of fast food restaurants adding calorie labelling to menu items on the energy content of individual purchases. Design Cross sectional surveys in spring 2007 and spring 2009 (one year before and nine months after full implementation of regulation requiring chain restaurants’ menus to contain details of the energy content of all menu items). Setting 168 randomly selected locations of the top 11 fast food chains in New York City during lunchtime hours. Participants 7309 adult customers interviewed in 2007 and 8489 in 2009. Main outcome measures Energy content of individual purchases, based on customers’ register receipts and on calorie information provided for all items in menus. Results For the full sample, mean calories purchased did not change from before to after regulation (828 v 846 kcal, P=0.22), though a modest decrease was shown in a regression model adjusted for restaurant chain, poverty level for the store location, sex of customers, type of purchase, and inflation adjusted cost (847 v 827 kcal, P=0.01). Three major chains, which accounted for 42% of customers surveyed, showed significant reductions in mean energy per purchase (McDonald’s 829 v 785 kcal, P=0.02; Au Bon Pain 555 v 475 kcal, P<0.001; KFC 927 v 868 kcal, P<0.01), while mean energy content increased for one chain (Subway 749 v 882 kcal, P<0.001). In the 2009 survey, 15% (1288/8489) of customers reported using the calorie information, and these customers purchased 106 fewer kilocalories than customers who did not see or use the calorie information (757 v 863 kcal, P<0.001). Conclusion Although no overall decline in calories purchased was observed for the full sample, several major chains saw significant reductions. After regulation, one in six lunchtime customers used the calorie information provided, and these customers made lower calorie choices.

What people buy from fast-food restaurants: caloric content and menu item selection, New York City 2007.

Fast‐food restaurants provide a growing share of daily food intake, but little information is available in the public health literature about customer purchases. In order to establish baseline data on mean calorie intake, this study was completed in the Spring of 2007, before calorie labeling regulations went into effect in New York City. Receipts were collected from lunchtime customers, at randomly selected New York City fast‐food chains. A supplementary survey was also administered to clarify receipt items. Calorie information was obtained through company websites and ascribed to purchases. Lunchtime purchases for 7,750 customers averaged 827 calories and were lowest for sandwich chains (734 calories); and highest for chicken chains (931 calories). Overall, one‐third of purchases were over 1,000 calories, predominantly from hamburger chains (39%) and chicken chains (48%); sandwich chains were the lowest, with only 20% of purchases over 1,000 calories. “Combination meals” at hamburger chains accounted for 31% of all purchases and averaged over 1,200 calories; side orders accounted for almost one‐third of these calories. Lunch meals at these fast‐food chains are high in calorie content. Although calorie posting may help to raise awareness of the high calories in fast‐food offerings, reducing portion sizes and changing popular combination meals to include lower calorie options could significantly reduce the average calorie content of purchases.

The Impact of New York City’s Health Bucks Program on Electronic Benefit Transfer Spending at Farmers Markets, 2006–2009

Introduction Increasing the accessibility and affordability of fresh produce is an important strategy for municipalities combatting obesity and related health conditions. Farmers markets offer a promising venue for intervention in urban settings, and in recent years, an increasing number of programs have provided financial incentives to Supplemental Nutrition Assistance Program (SNAP) recipients. However, few studies have explored the impact of these programs on use of SNAP benefits at farmers markets. Methods New York City’s Health Bucks Program provides SNAP recipients with a

Severe Obesity Among Children in New York City Public Elementary and Middle Schools, School Years 2006–07 Through 2010–11

2 coupon for every

A menu for health: changes to New York City school food, 2001 to 2011.

5 spent using SNAP benefits at participating farmers markets. We analyzed approximately 4 years of electronic benefit transfer (EBT) sales data, from July 2006 through November 2009, to develop a preliminary assessment of the effect of the Health Bucks Program on EBT spending at participating markets. Results Farmers markets that offered Health Bucks coupons to SNAP recipients averaged higher daily EBT sales than markets without the incentive (

Measurement of Compliance With New York City’s Regulations on Beverages, Physical Activity, and Screen Time in Early Child Care Centers

383.07, 95% confidence interval [CI], 333.1–433.1, vs

Pushing Produce: The New York City Green Carts Initiative

273.97, 95% CI, 243.4–304.5, P < 0.001) following the introduction of a direct point-of-purchase incentive. Multivariate analysis indicated this difference remained after adjusting for the year the market was held and the neighborhood poverty level. Conclusion When a

Reducing Sugary Drink Consumption: New York City’s Approach

2 financial incentive was distributed with EBT, use of SNAP benefits increased at participating New York City farmers markets. We encourage other urban jurisdictions to consider adapting the Health Bucks Program to encourage low-income shoppers to purchase fresh produce as one potential strategy in a comprehensive approach to increasing healthful food access and affordability in low-income neighborhoods.

The Effects of Changes in Physical Fitness on Academic Performance Among New York City Youth

Introduction Although studies have shown that childhood obesity overall is on the decline among New York City (NYC) public school children, the prevalence of severe childhood obesity has not been studied. Methods We used height and weight measurements of 947,765 NYC public school students aged 5 to 14 years in kindergarten through 8th grade (K–8), from school years 2006–07 through 2010–11. We used age- and sex-specific body mass index (BMI) percentiles according to Centers for Disease Control and Prevention growth charts to define childhood obesity (BMI ≥ 95th percentile) and severe childhood obesity (BMI ≥120% of 95th percentile) and to identify biologically implausible values (BIV). Multivariable logistic models tested for trends in obesity and severe obesity prevalence. To evaluate misclassification, we recalculated prevalence estimates for the most recent school year (2010–11) including the student records identified as BIV who were also declared severely obese (BMI ≥ 120% of 95th percentile). We refer to this subgroup of BIVs as “high BIV.” Results Severe obesity among NYC public school students in grades K–8 decreased 9.5% from the 2006–07 school year (6.3%) to the 2010–11 school year (5.7%), and obesity decreased 5.5% (from 21.9% to 20.7%). The prevalence of severe obesity and obesity was highest among minority, poor, and male children. Severe obesity declined in prevalence among every subgroup, with the greatest effect among white students and wealthy students. Severe obesity prevalence increased with age, and obesity prevalence peaked among those aged 7 to 10 years. For the 2010–11 school year, including high BIVs increased severe obesity prevalence from 5.7% to 6.6% and increased obesity prevalence from 20.7% to 21.5%. Conclusion Among all subgroups of NYC public school children in grades K–8, the reduction in severe obesity was greater than the reduction in overall obesity. Efforts to decrease obesity in NYC have affected the severely obese; however, monitoring of this specific subgroup should continue because of differences in trends and greater health risks.