Sarah Moreland-Russell

A Systematic Review of Neighborhood Disparities in Point-of-Sale Tobacco Marketing

We systematically reviewed evidence of disparities in tobacco marketing at tobacco retailers by sociodemographic neighborhood characteristics. We identified 43 relevant articles from 893 results of a systematic search in 10 databases updated May 28, 2014. We found 148 associations of marketing (price, placement, promotion, or product availability) with a neighborhood demographic of interest (socioeconomic disadvantage, race, ethnicity, and urbanicity). Neighborhoods with lower income have more tobacco marketing. There is more menthol marketing targeting urban neighborhoods and neighborhoods with more Black residents. Smokeless tobacco products are targeted more toward rural neighborhoods and neighborhoods with more White residents. Differences in store type partially explain these disparities. There are more inducements to start and continue smoking in lower-income neighborhoods and in neighborhoods with more Black residents. Retailer marketing may contribute to disparities in tobacco use. Clinicians should be aware of the pervasiveness of these environmental cues.

Update on Health Literacy and Diabetes

Purpose Inadequate literacy is common among patients with diabetes and may lead to adverse outcomes. The authors reviewed the relationship between literacy and health outcomes in patients with diabetes and potential interventions to improve outcomes. Methods We reviewed 79 articles covering 3 key domains: (1) evaluation of screening tools to identify inadequate literacy and numeracy, (2) the relationships of a range of diabetes-related health outcomes with literacy and numeracy, and (3) interventions to reduce literacy-related differences in health outcomes. Results Several screening tools are available to assess patients’ print literacy and numeracy skills, some specifically addressing diabetes. Literacy and numeracy are consistently associated with diabetes-related knowledge. Some studies suggest literacy and numeracy are associated with intermediate outcomes, including self-efficacy, communication, and self-care (including adherence), but the relationship between literacy and glycemic control is mixed. Few studies have assessed more distal health outcomes, including diabetes-related complications, health care utilization, safety, or quality of life, but available studies suggest low literacy may be associated with increased risk of complications, including hypoglycemia. Several interventions appear to be effective in improving diabetes-related outcomes regardless of literacy status, but it is unclear if these interventions can reduce literacy-related differences in outcomes. Conclusions Low literacy is associated with less diabetes-related knowledge and may be related to other important health outcomes. Further studies are needed to better elucidate pathways by which literacy skills affect health outcomes. Promising interventions are available to improve diabetes outcomes for patients with low literacy; more research is needed to determine their effectiveness outside of research settings.

Tweeting for and against public health policy: response to the Chicago Department of Public Health's electronic cigarette Twitter campaign.

Background In January 2014, the Chicago City Council scheduled a vote on local regulation of electronic cigarettes as tobacco products. One week prior to the vote, the Chicago Department of Public Health (CDPH) released a series of messages about electronic cigarettes (e-cigarettes) through its Twitter account. Shortly after the messages, or tweets, were released, the department’s Twitter account became the target of a “Twitter bomb” by Twitter users sending more than 600 tweets in one week against the proposed regulation. Objective The purpose of our study was to examine the messages and tweet patterns in the social media response to the CDPH e-cigarette campaign. Methods We collected all tweets mentioning the CDPH in the week between the e-cigarette campaign and the vote on the new local e-cigarette policy. We conducted a content analysis of the tweets, used descriptive statistics to examine characteristics of involved Twitter users, and used network visualization and descriptive statistics to identify Twitter users prominent in the conversation. Results Of the 683 tweets mentioning CDPH during the week, 609 (89.2%) were anti-policy. More than half of anti-policy tweets were about use of electronic cigarettes for cessation as a healthier alternative to combustible cigarettes (358/609, 58.8%). Just over one-third of anti-policy tweets asserted that the health department was lying or disseminating propaganda (224/609, 36.8%). Approximately 14% (96/683, 14.1%) of the tweets used an account or included elements consistent with “astroturfing”—a strategy employed to promote a false sense of consensus around an idea. Few Twitter users were from the Chicago area; Twitter users from Chicago were significantly more likely than expected to tweet in support of the policy. Conclusions Our findings may assist public health organizations to anticipate, recognize, and respond to coordinated social media campaigns.

Communication About Childhood Obesity on Twitter

OBJECTIVES Little is known about the use of social media as a tool for health communication. We used a mixed-methods design to examine communication about childhood obesity on Twitter. METHODS NodeXL was used to collect tweets sent in June 2013 containing the hashtag #childhoodobesity. Tweets were coded for content; tweeters were classified by sector and health focus. Data were also collected on the network of follower connections among the tweeters. We used descriptive statistics and exponential random graph modeling to examine tweet content, characteristics of tweeters, and the composition and structure of the network of connections facilitating communication among tweeters. RESULTS We collected 1110 tweets originating from 576 unique Twitter users. More individuals (65.6%) than organizations (32.9%) tweeted. More tweets focused on individual behavior than environment or policy. Few government and educational tweeters were in the network, but they were more likely than private individuals to be followed by others. CONCLUSIONS There is an opportunity to better disseminate evidence-based information to a broad audience through Twitter by increasing the presence of credible sources in the #childhoodobesity conversation and focusing the content of tweets on scientific evidence.

The Program Sustainability Assessment Tool: A New Instrument for Public Health Programs

Introduction Public health programs can deliver benefits only if they are able to sustain programs, policies, and activities over time. Although numerous sustainability frameworks and models have been developed, there are almost no assessment tools that have demonstrated reliability or validity or have been widely disseminated. We present the Program Sustainability Assessment Tool (PSAT), a new and reliable instrument for assessing the capacity for program sustainability of various public health and other programs. Methods A measurement development study was conducted to assess the reliability of the PSAT. Program managers and staff (n = 592) representing 252 public health programs used the PSAT to rate the sustainability of their program. State and community-level programs participated, representing 4 types of chronic disease programs: tobacco control, diabetes, obesity prevention, and oral health. Results The final version of the PSAT contains 40 items, spread across 8 sustainability domains, with 5 items per domain. Confirmatory factor analysis shows good fit of the data with the 8 sustainability domains. The subscales have excellent internal consistency; the average Cronbach’s α is 0.88, ranging from 0.79 to 0.92. Preliminary validation analyses suggest that PSAT scores are related to important program and organizational characteristics. Conclusion The PSAT is a new and reliable assessment instrument that can be used to measure a public health program’s capacity for sustainability. The tool is designed to be used by researchers, evaluators, program managers, and staff for large and small public health programs.

Disparities and Menthol Marketing: Additional Evidence in Support of Point of Sale Policies

This study examined factors associated with point-of-sale tobacco marketing in St. Louis, an urban city in the United States. Using spatial analysis, descriptive statistics, and multilevel modeling, we examined point-of-sale data and the proportion of mentholated cigarette and total cigarette marketing from 342 individual tobacco retail stores within St. Louis census tracts characterized by the percent of black adults and children. Menthol and total tobacco product marketing was highest in areas with the highest percentages of black residents. When examining menthol marketing to children, we did not find as strong of a relationship, however results of multilevel modeling indicate that as the proportion of black children in a census tract increased, the proportion of menthol marketing near candy also increased. These results indicate the need for communities globally to counter this targeted marketing by taking policy action specifically through the enactment of marketing restrictions provided by the 2009 Family Smoking Prevention and Tobacco Control Act and the Framework Convention of Tobacco Control.

Diabetes topics associated with engagement on Twitter

Introduction Social media are widely used by the general public and by public health and health care professionals. Emerging evidence suggests engagement with public health information on social media may influence health behavior. However, the volume of data accumulating daily on Twitter and other social media is a challenge for researchers with limited resources to further examine how social media influence health. To address this challenge, we used crowdsourcing to facilitate the examination of topics associated with engagement with diabetes information on Twitter. Methods We took a random sample of 100 tweets that included the hashtag “#diabetes” from each day during a constructed week in May and June 2014. Crowdsourcing through Amazon’s Mechanical Turk platform was used to classify tweets into 9 topic categories and their senders into 3 Twitter user categories. Descriptive statistics and Tweedie regression were used to identify tweet and Twitter user characteristics associated with 2 measures of engagement, “favoriting” and “retweeting.” Results Classification was reliable for tweet topics and Twitter user type. The most common tweet topics were medical and nonmedical resources for diabetes. Tweets that included information about diabetes-related health problems were positively and significantly associated with engagement. Tweets about diabetes prevalence, nonmedical resources for diabetes, and jokes or sarcasm about diabetes were significantly negatively associated with engagement. Conclusion Crowdsourcing is a reliable, quick, and economical option for classifying tweets. Public health practitioners aiming to engage constituents around diabetes may want to focus on topics positively associated with engagement.

Using the Program Sustainability Assessment Tool to Assess and Plan for Sustainability

Implementing and growing a public health program that benefits society takes considerable time and effort. To ensure that positive outcomes are maintained over time, program managers and stakeholders should plan and implement activities to build sustainability capacity within their programs. We describe a 3-part sustainability planning process that programs can follow to build their sustainability capacity. First, program staff and stakeholders take the Program Sustainability Assessment Tool to measure their program’s sustainability across 8 domains. Next, managers and stakeholders use results from the assessment to inform and prioritize sustainability action planning. Lastly, staff members implement the plan and keep track of progress toward their sustainability goals. Through this process, staff can more holistically address the internal and external challenges and pressures associated with sustaining a program. We include a case example of a chronic disease program that completed the Program Sustainability Assessment Tool and engaged in program sustainability planning.

Social network analysis of public health programs to measure partnership

In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce tobacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the networks, we conducted comparative analyses with and without adjustment for network size. SIM programs had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes.

Breaking down silos: mapping growth of cross-disciplinary collaboration in a translational science initiative.

The importance of transdisciplinary collaboration is growing, though not much is known about how to measure collaboration patterns. The purpose of this paper is to present multiple ways of mapping and evaluating the growth of cross‐disciplinary partnerships over time. Social network analysis was used to examine the impact of a Clinical and Translational Science Award (CTSA) on collaboration patterns. Grant submissions from 2007 through 2010 and publications from 2007 through 2011 of Institute of Clinical and Translational Sciences (ICTS) members were examined. A Cohort Model examining the first‐year ICTS members demonstrated an overall increase in collaborations on grants and publications, as well as an increase in cross‐discipline collaboration as compared to within‐discipline. A Growth Model that included additional members over time demonstrated the same pattern for grant submissions, but a decrease in cross‐discipline collaboration as compared to within‐discipline collaboration for publications. ICTS members generally became more cross‐disciplinary in their collaborations during the CTSA. The exception of publications for the Growth Model may be due to the time lag between funding and publication, as well as pressure for younger scientists to publish in their own fields. Network analysis serves as a valuable tool for evaluating changes in scientific collaboration.