Faculty Bibliography

Objective: Identify consumer characteristics that predict seeing and using calorie information on fast food menu boards. Methods: Two separate data collection methods were used in Philadelphia during June 2010, several weeks after calorie labeling legislation went into effect: (1) point-of-purchase survey and receipt collection conducted outside fast food restaurants (N = 669) and (2) a random digit dial telephone survey (N = 702). Logistic regressions were used to predict the odds of reporting seeing, and of reporting seeing and being influenced by posted calorie information. Results: Approximately 35.1% of point-of-purchase and 65.7% of telephone survey respondents reported seeing posted calorie information, 11.8% and 41.7%, respectively, reported that the labels influenced their purchasing decisions, and 8.4% and 17% reported they were influenced in a healthful direction. BMI, education, income, gender, consumer preferences, restaurant chain, and frequency of visiting fast food restaurants were associated with heterogeneity in the likelihood of reporting seeing and reporting seeing and using calorie labels. Conclusion: Demographic characteristics and consumer preferences are important determinants in the use of posted calorie information. Future work should consider the types of consumers this information is intended for, and how to effectively reach them.

In 2012, fast-food companies spent $4.6 billion on ads, while $116 million was spent advertising fruits and vegetables. Because young people see tons of food ads on adult-targeted programs, it makes sense to cite the whole $4.6 billion figure

BackgroundStudies rarely find fewer calories purchased following calorie labeling implementation. However, few studies consider whether estimates of the number of calories purchased improved following calorie labeling legislation.FindingsResearchers surveyed customers and collected purchase receipts at fast food restaurants in the United States cities of Philadelphia (which implemented calorie labeling policies) and Baltimore (a matched comparison city) in December 2009 (pre-implementation) and June 2010 (post-implementation). A difference-in-difference design was used to examine the difference between estimated and actual calories purchased, and the odds of underestimating calories.Participants in both cities, both pre- and post-calorie labeling, tended to underestimate calories purchased, by an average 216 inverted question mark409 calories. Adjusted difference-in-differences in estimated-actual calories were significant for individuals who ordered small meals and those with some college education (accuracy in Philadelphia improved by 78 and 231 calories, respectively, relative to Baltimore, p inverted question mark= inverted question mark0.03-0.04). However, categorical accuracy was similar; the adjusted odds ratio [AOR] for underestimation by >100 calories was 0.90 (p inverted question mark= inverted question mark0.48) in difference-in-difference models. Accuracy was most improved for subjects with a BA or higher education (AOR inverted question mark= inverted question mark0.25, p inverted question mark< inverted question mark0.001) and for individuals ordering small meals (AOR inverted question mark= inverted question mark0.54, p inverted question mark= inverted question mark0.001). Accuracy worsened for females (AOR inverted question mark= inverted question mark1.38, p inverted question mark< inverted question mark0.001) and for individuals ordering large meals (AOR inverted question mark= inverted question mark1.27, p inverted question mark= inverted question mark0.028).ConclusionsWe concluded that the odds of underestimating calories varied by subgroup, suggesting that at some level, consumers may incorporate labeling information.

OBJECTIVES: Despite the increased focus on health care consumers' active choice, not enough is known about how to best facilitate the choice process. We sought to assess methods of improving this process for vulnerable consumers in the United States by testing alternatives that emphasize insights from behavioral economics, or 'nudges'. METHODS: We performed a hypothetical choice experiment where subjects were randomized to one of five experimental conditions and asked to choose a health center (location where they would receive all their care). The conditions presented the same information about health centers in different ways, including graphically as a chart, via written summary and using behavioral economics, 'nudging' consumers toward particular choices. We hypothesized that these 'nudges' might help simplify the choice process. Our primary outcomes focused on the health center chosen and whether consumers were willing to accept 'nudges'. RESULTS: We found that consumer choice was influenced by the method of presentation and the majority of consumers accepted the health center they were 'nudged' towards. CONCLUSIONS: Consumers were accepting of choices grounded in insights from behavioral economics and further consideration should be given to their role in patient choice.

In March 2013 a state judge invalidated New York City's proposal to ban sales of sugar-sweetened beverages larger than 16 ounces; the case is under appeal. This setback was attributable in part to opposition from the beverage industry and racial/ethnic minority organizations they support. We provide lessons from similar tobacco industry efforts to block policies that reduced smoking prevalence. We offer recommendations that draw on the tobacco control movement's success in thwarting industry influence and promoting public health policies that hold promise to improve population health.

OBJECTIVE: Obesity is a pressing public health problem without proven population-wide solutions. Researchers sought to determine whether a city-mandated policy requiring calorie labeling at fast food restaurants was associated with consumer awareness of labels, calories purchased and fast food restaurant visits. DESIGN AND METHODS: Difference-in-differences design, with data collected from consumers outside fast food restaurants and via a random digit dial telephone survey, before (December 2009) and after (June 2010) labeling in Philadelphia (which implemented mandatory labeling) and Baltimore (matched comparison city). Measures included: self-reported use of calorie information, calories purchased determined via fast food receipts, and self-reported weekly fast-food visits. RESULTS: The consumer sample was predominantly Black (71%), and high school educated (62%). Postlabeling, 38% of Philadelphia consumers noticed the calorie labels for a 33% point (P < 0.001) increase relative to Baltimore. Calories purchased and number of fast food visits did not change in either city over time. CONCLUSIONS: While some consumers report noticing and using calorie information, no population level changes were noted in calories purchased or fast food visits. Other controlled studies are needed to examine the longer term impact of labeling as it becomes national law.

BACKGROUND: To induce consumers to purchase healthier foods and beverages, some policymakers have suggested special taxes or labels on unhealthy products. The potential of such policies is unknown. PURPOSE: In a controlled field experiment, researchers tested whether consumers were more likely to purchase healthy products under such policies. METHODS: From October to December 2011, researchers opened a store at a large hospital that sold a variety of healthier and less-healthy foods and beverages. Purchases (N=3680) were analyzed under five conditions: a baseline with no special labeling or taxation, a 30% tax, highlighting the phrase "less healthy" on the price tag, and combinations of taxation and labeling. Purchases were analyzed in January-July 2012, at the single-item and transaction levels. RESULTS: There was no significant difference between the various taxation conditions. Consumers were 11 percentage points more likely to purchase a healthier item under a 30% tax (95% CI=7%, 16%, p<0.001) and 6 percentage points more likely under labeling (95% CI=0%, 12%, p=0.04). By product type, consumers switched away from the purchase of less-healthy food under taxation (9 percentage point decrease, p<0.001) and into healthier beverages (6 percentage point increase, p=0.001); there were no effects for labeling. Conditions were associated with the purchase of 11-14 fewer calories (9%-11% in relative terms) and 2 fewer grams of sugar. Results remained significant controlling for all items purchased in a single transaction. CONCLUSIONS: Taxation may induce consumers to purchase healthier foods and beverages. However, it is unclear whether the 15%-20% tax rates proposed in public policy discussions would be more effective than labeling products as less healthy.

Obesity is a prominent public health concern that disproportionally affects low-income and minority populations. Recent policies mandating the posting of calories on menus in fast-food chain restaurants have not proven to uniformly influence food choice. This qualitative research study used focus groups to study individual and environmental factors affecting the use of these menu labels among low-income minority populations. Ten focus groups targeting low-income residents (n=105) were held at various community organizations throughout New York City over a 9-month period in 2011. The focus groups were conducted in Spanish, English, or a combination of both languages. In late 2011 and early 2012, transcripts were coded through the process of thematic analysis using Atlas.ti for naturally emerging themes, influences, and determinants of food choice. Few participants used menu labels, despite awareness. The most frequently cited as barriers to menu label use included: price and time constraints, confusion and lack of understanding about caloric values, as well as the priority of preference, hunger, and habitual ordering habits. Based on the individual and external influences on food choice that often take priority over calorie consideration, a modified approach may be necessary to make menu labels more effective and user-friendly.

BACKGROUND: This paper describes an innovative protocol for a type-II hybrid effectiveness-implementation trial that is evaluating a smoking cessation telephone care coordination program for Veterans Health Administration (VA) mental-health clinic patients. As a hybrid trial, the protocol combines implementation science and clinical trial methods and outcomes that can inform future cessation studies and the implementation of tobacco cessation programs into routine care. The primary objectives of the trial are (1) to evaluate the process of adapting, implementing, and sustaining a smoking cessation telephone care coordination program in VA mental health clinics, (2) to determine the effectiveness of the program in promoting long-term abstinence from smoking among mental health patients, and (3) to compare the effectiveness of telephone counseling delivered by VA staff with that delivered by state quitlines. METHODS/DESIGN: The care coordination program is being implemented at six VA facilities. VA mental health providers refer patients to the program via an electronic medical record consult. Program staff call referred patients to offer enrollment. All patients who enroll receive a self-help booklet, mailed smoking cessation medications, and proactive multi-call telephone counseling. Participants are randomized to receive this counseling from VA staff or their state's quitline. Four primary implementation strategies are being used to optimize program implementation and sustainability: blended facilitation, provider training, informatics support, and provider feedback. A three-phase formative evaluation is being conducted to identify barriers to, and facilitators for, program implementation and sustainability. A mixed-methods approach is being used to collect quantitative clinical effectiveness data (e.g., self-reported abstinence at six months) and both quantitative and qualitative implementation data (e.g., provider referral rates, coded interviews with providers). Summative data will be analyzed using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. DISCUSSION: This paper describes the rationale and methods of a trial designed to simultaneously study the clinical effectiveness and implementation of a telephone smoking cessation program for smokers using VA mental health clinics. Such hybrid designs are an important methodological design that can shorten the time between the development of an intervention and its translation into routine clinical care. TRIAL REGISTRATION: ClinicalTrials.gov NCT00724308.