Using Social Media to Identify Sources of Healthy Food in Urban Neighborhoods

GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies

The industrial revolution and urbanization fundamentally restructured populations' living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies.

Designing and Evaluating a Hierarchical Framework for Matching Food Outlets across Multi-sourced Geospatial Datasets: a Case Study of San Diego County

Research on retail food environment (RFE) relies on data availability and accuracy. However, the discrepancies in RFE datasets may lead to imprecision when measuring association with health outcomes. In this research, we present a two-tier hierarchical point of interest (POI) matching framework to compare and triangulate food outlets across multiple geospatial data sources. Two matching parameters were used including the geodesic distance between businesses and the similarity of business names according to Levenshtein distance (LD) and Double Metaphone (DM). Sensitivity analysis was conducted to determine thresholds of matching parameters. Our Tier 1 matching used more restricted parameters to generate high confidence-matched POIs, whereas in Tier 2 we opted for relaxed matching parameters and applied a weighted multi-attribute model on the previously unmatched records. Our case study in San Diego County, California used government, commercial, and crowdsourced data and returned 20.2% matched records from Tier 1 and 18.6% matched from Tier 2. Our manual validation shows a 100% matching rate for Tier 1 and up to 30.6% for Tier 2. Matched and unmatched records from Tier 1 were further analyzed for spatial patterns and categorical differences. Our hierarchical POI matching framework generated highly confident food POIs by conflating datasets and identified some food POIs that are unique to specific data sources. Triangulating RFE data can reduce uncertain and invalid POI listings when representing food environment using multiple data sources. Studies investigating associations between food environment and health outcomes may benefit from improved quality of RFE.

Measuring food insecurity: An introduction to tools for human biologists and ecologists

OBJECTIVE

Food insecurity is a significant and growing concern undermining the wellbeing of 30% of the global population. Food in/security is a complex construct consisting of four dimensions: availability, access, utilization, and stability, making it challenging to measure. We provide a toolkit human biologists/ecologists can use to advance research on this topic.

METHODS

We review the strengths and limitations of common tools used to measure food access and utilization, the two dimensions most proximate to people's lived experience, and emphasize tools that provide data needed to best link food security with human biological outcomes. We also discuss methods that provide contextual data human biologists/ecologists will find useful for study design, ensuring instrument validity, and improving data quality.

RESULTS

Food access is principally measured using experience-based instruments that emphasize economic access. Social access, such as food sharing, is under-studied and we recommend using social network analysis to explore this dimension. In terms of utilization, emphasis has been on food choice measured as dietary diversity. Food preparation and intrahousehold distribution, also part of the utilization dimension, are less studied and standardized instruments for measuring both are lacking. The embodiment of food insecurity has focused on child growth, although a growing literature addresses adult mental wellbeing and chronic and infectious disease risk.

CONCLUSIONS

We see the potential to expand outcomes to include reproductive and immune function, physical activity, and the gut microbiome. Human biologists/ecologists are well-positioned to advance understanding of the human health impacts of food insecurity and provide data to support intervention efforts.

Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination

During the crisis of Coronavirus pandemic, social media, like Twitter, have been the platforms on which people have been able to share their opinions and obtain information. The present study provides a detailed spatial-temporal analysis of the Twitter online discourse (approximately 280 thousand tweets) in Ohio and Michigan at the early stage of vaccination rollout (January 2021, till March 2021). This work aims to explore how people were feeling about the pandemic, the most frequent topics people were talking about, and how the topics spatially were distributed. Moreover, state government responses and important news were gathered to analyze their impacts on public opinion based on the temporal analysis of the tweets. In this project, Natural Language Processing using the LDA method was employed to identify 11 topics and 8 sub-topics in the Twitter data. The temporal analysis of topics shows the sensitivity of the online discourse to the significant state news and the local government's reactions to the pandemic. Moreover, the spatial distribution of Coronavirus-related tweets and sentiments demonstrates concentrations in the more populated urban areas with a high rate of COVID-19 cases in Ohio and Michigan. The government's economic and financial policies taken during this time, the vaccination timeline phases specified by each state, and the pandemic-related information can contribute to public opinion and sentiment trends. The findings of this study can help explore public demands, and reactions, follow the impacts of the local authorities' policies at the county level and manage their future responses to such a pandemic.

Examining the Factors That Affect Consumers’ Purchase Intention of Organic Food Products in a Developing Country

The purpose of this article is to investigate the factors that influence consumers’ intention to purchase organic food in Egypt. Given the novelty of organic food marketing in developing countries, much of the factors that influence its consumption are still inadequately explored in the marketing literature. A conceptual model of the factors that impact the consumption of organic food was developed based on the theory of planned behaviour and previous literature in the area of food consumption. To test the conceptual model and to validate the research hypotheses, an online questionnaire was adopted to collect data from 363 consumers in Egypt. The partial least square structural equation modelling (PLS-SEM) approach was used to analyse the data. The findings indicated that purchase intention of organic food is influenced by consumers’ attitudes and environmental concern. However, e-WOM, subjective norms, perceived behavioural control and health consciousness did not influence consumers’ purchase intention. Conversely, the results showed that e-WOM had a significant influence on consumers’ attitudes, subjective norms, perceived behavioural control, health consciousness and environmental concern. This article contributes by presenting the factors that affect organic food purchase intention in Egypt, and it provides some recommendations for marketing organic food in developing countries.

Food insecurity in Detroit: exploring the relationship between patient-reported food insecurity and proximity to healthful grocery stores

OBJECTIVE

The objective of the current study was to determine if patients of a large health care system in Detroit who self-identify as food insecure live further away from healthy grocery stores compared with food secure patients. Second, we explored whether food insecurity and distance to healthy grocery stores are related to ecological measures of vehicle availability in the area of residence.

DESIGN

A secondary data analysis that uses baseline data from a pilot intervention/feasibility study.

SETTING

Detroit, Michigan, USA.

PARTICIPANTS

Patients of Henry Ford Health System were screened for food insecurity to determine eligibility for a pilot intervention/feasibility study (i.e. Henry's Groceries for Health), conducted through a collaboration with Gleaners Community Foodbank of Southeastern Michigan. Only patients residing in Detroit city limits (including Highland Park and Hamtramck) were included in the secondary analysis. Of the 1,100 patients included in the analysis, 336 (31 %) were food insecure.

RESULTS

After accounting for socio-demographic factors associated with food insecurity, we did not find evidence that food insecure patients lived further away from healthier grocery stores, nor was this modified by ecological measures of vehicle access. However, some neighbourhoods were identified as having a significantly higher risk of food insecurity.

CONCLUSIONS

Food insecure patients in Detroit are perhaps limited by social and political determinants and not their immediate neighbourhood geography or physical access to healthy grocery stores. Future research should explore the complexity in linkages between household socio-economic factors, socio-cultural dynamics and the neighbourhood food environment.

Large-scale diet tracking data reveal disparate associations between food environment and diet

An unhealthy diet is a major risk factor for chronic diseases including cardiovascular disease, type 2 diabetes, and cancer1-4. Limited access to healthy food options may contribute to unhealthy diets5,6. Studying diets is challenging, typically restricted to small sample sizes, single locations, and non-uniform design across studies, and has led to mixed results on the impact of the food environment7-23. Here we leverage smartphones to track diet health, operationalized through the self-reported consumption of fresh fruits and vegetables, fast food and soda, as well as body-mass index status in a country-wide observational study of 1,164,926 U.S. participants (MyFitnessPal app users) and 2.3 billion food entries to study the independent contributions of fast food and grocery store access, income and education to diet health outcomes. This study constitutes the largest nationwide study examining the relationship between the food environment and diet to date. We find that higher access to grocery stores, lower access to fast food, higher income and college education are independently associated with higher consumption of fresh fruits and vegetables, lower consumption of fast food and soda, and lower likelihood of being affected by overweight and obesity. However, these associations vary significantly across zip codes with predominantly Black, Hispanic or white populations. For instance, high grocery store access has a significantly larger association with higher fruit and vegetable consumption in zip codes with predominantly Hispanic populations (7.4% difference) and Black populations (10.2% difference) in contrast to zip codes with predominantly white populations (1.7% difference). Policy targeted at improving food access, income and education may increase healthy eating, but intervention allocation may need to be optimized for specific subpopulations and locations.

Exploring food shopping behaviours through a study of Ottawa social media

This study explored the important attributes of the local food retail environments that residents from Ottawa, Ontario, Canada, used in recommending where to purchase fresh produce, including fruits and vegetables, in the Ottawa area. Drawing upon an approach originating in marketing and consumer research, qualitative thematic analysis was used to analyze 79 discussions from three social media platforms that occurred between 2015 and 2018. We identified three patterns of conversations about food shopping, characterized by participants describing important factors of their local retail food environments that shaped their recommendations for different retail food establishments: 1) Pleasant represented discussions where having a pleasurable food shopping experience was the main discussion point. 2) Thrifty discussions were marked primarily by economical management and discussed food shopping in pragmatic terms. 3) Compromise represented a group where discussions described needing to find a middle ground between affordability and quality. While not without limitations, our study was the first exploration of whether social media data could be useful for qualitatively evaluating local retail food environments. Our findings add to the conclusions of other researchers that social media data does not compromise on the breadth of views captured and can parallel findings from traditional methods. These findings have implications for nutrition researchers and practitioners who we encourage to consider social media discussion data in their work.

Opportunities for Qualitative Analysis of Social Media Platforms in Dietetic Research and Practice

To date, most qualitative knowledge about individual eating patterns and the food environment has been derived from traditional data collection methods, such as interviews, focus groups, and observations. However, there currently exists a large source of nutrition-related data in social media discussions that have the potential to provide opportunities to improve dietetic research and practice. Qualitative social media discussion analysis offers a new tool for dietetic researchers and practitioners to gather insights into how the public discusses various nutrition-related topics. We first consider how social media discussion data come with significant advantages including low-cost access to timely ways to gather insights from the public, while also cautioning that social media data have limitations (e.g., difficulty verifying demographic information). We then outline 3 types of social media discussion platforms in particular: (i) online news article comment sections, (ii) food and nutrition blogs, and (iii) discussion forums. We discuss how each different type of social media offers unique insights and provide a specific example from our own research using each platform. We contend that social media discussions can contribute positively to dietetic research and practice.

Social Media Use for Health Purposes: Systematic Review

Background

Social media has been widely used for health-related purposes, especially during the COVID-19 pandemic. Previous reviews have summarized social media uses for a specific health purpose such as health interventions, health campaigns, medical education, and disease outbreak surveillance. The most recent comprehensive review of social media uses for health purposes, however, was conducted in 2013. A systematic review that covers various health purposes is needed to reveal the new usages and research gaps that emerge in recent years.

Objective

This study aimed to provide a systematic review of social media uses for health purposes that have been identified in previous studies.

Methods

The researchers searched for peer-reviewed journal articles published between 2006 and 2020 in 12 databases covering medicine, public health, and social science. After coding the articles in terms of publication year, journal area, country, method, social media platform, and social media use for health purposes, the researchers provided a review of social media use for health purposes identified in these articles.

Results

This study summarized 10 social media uses for various health purposes by health institutions, health researchers and practitioners, and the public.

Conclusions

Social media can be used for various health purposes. Several new usages have emerged since 2013 including advancing health research and practice, social mobilization, and facilitating offline health-related services and events. Research gaps exist regarding advancing strategic use of social media based on audience segmentation, evaluating the impact of social media in health interventions, understanding the impact of health identity development, and addressing privacy concerns.

Crowdsourced Mapping for Healthy Food Accessibility in Dallas, Texas: A Feasibility Study

Since its first use for describing a neighborhood lacking access to food in the 1990's, “food deserts” has been widely addressed by researchers and adopted as an indicator of neighborhood-level food insecurity by governmental agencies, such as USDA. However, mostly due to cost and difficulty in collecting georeferenced data and characteristics of grocery stores, the USDA Food Access Research Atlas is infrequently released, and considers only income, vehicle ownership, and distance to the nearest grocery store. In this paper, we explored the feasibility of a crowdsourced geospatial data source, coupled with additional measures, in supplementing the USDA's current designation of food deserts. We used Yelp data to map food deserts in the city of Dallas and compared them with those based on the 2015 USDA food retailer database. Although direct comparison was not possible due to time mismatch between the two data sources, the discrepancies highlighted the need of a more frequent identification of food deserts for timely policy intervention. Furthermore, we extended mapping to reveal other potential areas of concerns, by adding the Transit Score metric and Yelp's price descriptor of businesses. The resulting maps illustrated the areas with grocery stores nearby but with limited accessibility due to lack of public transit or potential financial barriers in purchasing foods due to high prices. Our findings demonstrate the current status and future potential of up-to-date crowdsourced, georeferenced data as a complement of official government data, which could serve to extend food access research and guide health policies.

Assessing the Retail Food Environment in Madrid: An Evaluation of Administrative Data against Ground Truthing

Previous studies have suggested that European settings face unique food environment issues; however, retail food environments (RFE) outside Anglo-Saxon contexts remain understudied. We assessed the completeness and accuracy of an administrative dataset against ground truthing, using the example of Madrid (Spain). Further, we tested whether its completeness differed by its area-level socioeconomic status (SES) and population density. First, we collected data on the RFE through the ground truthing of 42 census tracts. Second, we retrieved data on the RFE from an administrative dataset covering the entire city (n = 2412 census tracts), and matched outlets using location matching and location/name matching. Third, we validated the administrative dataset against the gold standard of ground truthing. Using location matching, the administrative dataset had a high sensitivity (0.95; [95% CI = 0.89, 0.98]) and positive predictive values (PPV) (0.79; [95% CI = 0.70, 0.85]), while these values were substantially lower using location/name matching (0.55 and 0.45, respectively). Accuracy was slightly higher using location/name matching (k = 0.71 vs 0.62). We found some evidence for systematic differences in PPV by area-level SES using location matching, and in both sensitivity and PPV by population density using location/name matching. Administrative datasets may offer a reliable and cost-effective source to measure retail food access; however, their accuracy needs to be evaluated before using them for research purposes.

Using social media to assess the consumer nutrition environment: comparing Yelp reviews with a direct observation audit instrument for grocery stores

Objective

To examine the feasibility of using social media to assess the consumer nutrition environment by comparing sentiment expressed in Yelp reviews with information obtained from a direct observation audit instrument for grocery stores.

Design

Trained raters used the Nutrition Environment Measures Survey in Stores (NEMS-S) in 100 grocery stores from July 2015 to March 2016. Yelp reviews were available for sixty-nine of these stores and were retrieved in February 2017 using the Yelp Application Program Interface. A sentiment analysis was conducted to quantify the perceptions of the consumer nutrition environment in the review text. Pearson correlation coefficients (ρ) were used to compare NEMS-S scores with Yelp review text on food availability, quality, price and shopping experience.

Setting

Detroit, Michigan, USA.

Participants

None.

Results

Yelp reviews contained more comments about food availability and the overall shopping experience than food price and food quality. Negative sentiment about food prices in Yelp review text and the number of dollar signs on Yelp were positively correlated with observed food prices in stores (ρ=0·413 and 0·462, respectively). Stores with greater food availability were rated as more expensive on Yelp. Other aspects of the food store environment (e.g. overall quality and shopping experience) were captured only in Yelp.

Conclusions

While Yelp cannot replace in-person audits for collecting detailed information on the availability, quality and cost of specific food items, Yelp holds promise as a cost-effective means to gather information on the overall cost, quality and experience of food stores, which may be relevant for nutrition outcomes.

Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study

Background

Mobile devices are increasingly used to collect location-based information from individuals about their physical activities, dietary intake, environmental exposures, and mental well-being. Such research, which typically uses wearable devices or mobile phones to track location, benefits from the growing availability of fine-grained data regarding human mobility. However, little is known about the comparative geospatial accuracy of such devices.

Objective

In this study, we compared the data quality of location information collected from two mobile devices that determine location in different ways—a global positioning system (GPS) watch and a mobile phone with Google’s Location History feature enabled.

Methods

A total of 21 chronically ill participants carried both devices, which generated digital traces of locations, for 28 days. A mobile phone–based brief ecological momentary assessment (EMA) survey asked participants to manually report their location at 4 random times throughout each day. Participants also took part in qualitative interviews and completed surveys twice during the study period in which they reviewed recent mobile phone and watch trace data to compare the devices’ trace data with their memory of their activities on those days. Trace data from the devices were compared on the basis of (1) missing data days, (2) reasons for missing data, (3) distance between the route data collected for matching day and the associated EMA survey locations, and (4) activity space total area and density surfaces.

Results

The watch resulted in a much higher proportion of missing data days (P<.001), with missing data explained by technical differences between the devices as well as participant behaviors. The mobile phone was significantly more accurate in detecting home locations (P=.004) and marginally more accurate (P=.07) for all types of locations combined. The watch data resulted in a smaller activity space area and more accurately recorded outdoor travel and recreation.

Conclusions

The most suitable mobile device for location-based health research depends on the particular study objectives. Furthermore, data generated from mobile devices, such as GPS phones and smartwatches, require careful analysis to ensure quality and completeness. Studies that seek precise measurement of outdoor activity and travel, such as measuring outdoor physical activity or exposure to localized environmental hazards, would benefit from the use of GPS devices. Conversely, studies that aim to account for time within buildings at home or work, or those that document visits to particular places (such as supermarkets, medical facilities, or fast food restaurants), would benefit from the greater precision demonstrated by the mobile phone in recording indoor activities.