Evaluating Consumer Nutrition Environment in Food Deserts and Food Swamps

Jin, He; Lu, Yongmei

doi:10.3390/ijerph18052675

Cited by 23 publications

(76 citation statements)

References 31 publications

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“…At the time of this study, Guilford County aimed to become a smart, sustainable community. With a population of 533,670 within 645.70 square miles, it was the third most populated county in North Carolina and was also among the top five most densely populated counties in the state of North Carolina [20]. It was also the largest county in terms of acreage [38,39].…”

Section: Methodsmentioning

confidence: 99%

“…The availability of food sources is also very important. Food oases represent areas where people have an abundance of healthy food options rather than unhealthy food options [20]. In another study, the difference between food item prices was investigated with respect to food access areas, food deserts, food swamps, and food oases, and it was determined that there were no remarkable differences in the process [20].…”

Section: Introductionmentioning

confidence: 99%

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Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities

Almalki

Gokaraju

Mehta

et al. 2021

IJGI

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Food access is a major key component in food security, as it is every individual’s right to proper access to a nutritious and affordable food supply. Low access to healthy food sources influences people’s diet and activity habits. Guilford County in North Carolina has a high ranking in low food security and a high rate of health issues such as high blood pressure, high cholesterol, and obesity. Therefore, the primary objective of this study was to investigate the geospatial correlation between health issues and food access areas. The secondary objective was to quantitatively compare food access areas and heath issues’ descriptive statistics. The tertiary objective was to compare several machine learning techniques and find the best model that fit health issues against various food access variables with the highest performance accuracy. In this study, we adopted a food-access perspective to show that communities that have residents who have equitable access to healthy food options are typically less vulnerable to health-related disasters. We propose a methodology to help policymakers lower the number of health issues in Guilford County by analyzing such issues via correlation with respect to food access. Specifically, we conducted a geographic information system mapping methodology to examine how access to healthy food options influenced health and mortality outcomes in one of the largest counties in the state of North Carolina. We created geospatial maps representing food deserts—areas with scarce access to nutritious food; food swamps—areas with more availability of unhealthy food options compared to healthy food options; and food oases—areas with a relatively higher availability of healthy food options than unhealthy options. Our results presented a positive correlation coefficient of R2 = 0.819 among obesity and the independent variables of transportation access, and population. The correlation coefficient matrix analysis helped to identify a strong negative correlation between obesity and median income. Overall, this study offers valuable insights that can help health authorities develop preemptive preparedness for healthcare disasters.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities

Almalki

Gokaraju

Mehta

et al. 2021

IJGI

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“…These included NEMS-S-Rev (Nutrition Environment Measures Survey for Stores Revised), TxNEAS (Texas Nutrition Environment Assessment), NEMS-S-NL (Nutrition Environment Measures Survey for Stores Newfoundland and Labrador), and The Bridging the Gap Food Store Observation Form. This instrument was used mostly in the USA (n = 11) [11,33,36,44,47,48,54,57,68,71,107]. Studies were conducted in both rural (n = 4) [10,11,56,106] and urban (n = 11) [33,36,44,47,48,54,57,68,71,107,108] contexts.…”

Section: Nutrition Environment Measures Survey For Stores (Nems-s) In...mentioning

confidence: 99%

“…This instrument was used mostly in the USA (n = 11) [11,33,36,44,47,48,54,57,68,71,107]. Studies were conducted in both rural (n = 4) [10,11,56,106] and urban (n = 11) [33,36,44,47,48,54,57,68,71,107,108] contexts. Compared to the food basket methodology, the NEMS-S instrument compares products in the same category that are considered 'healthy' or 'unhealthy' based on American Dietetic Association (ADA) recommended dietary guidelines, focusing on availability, price, and quality.…”

Section: Nutrition Environment Measures Survey For Stores (Nems-s) In...mentioning

confidence: 99%

Assessing the Cost of Healthy and Unhealthy Diets: A Systematic Review of Methods

2022

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Purpose of Review Poor diets are a leading risk factor for chronic disease globally. Research suggests healthy foods are often harder to access, more expensive, and of a lower quality in rural/remote or low-income/high minority areas. Food pricing studies are frequently undertaken to explore food affordability. We aimed to capture and summarise food environment costing methodologies used in both urban and rural settings. Recent Findings Our systematic review of high-income countries between 2006 and 2021 found 100 relevant food pricing studies. Most were conducted in the USA (n = 47) and Australia (n = 24), predominantly in urban areas (n = 74) and cross-sectional in design (n = 76). All described a data collection methodology, with just over half (n = 57) using a named instrument. The main purpose for studies was to monitor food pricing, predominantly using the ‘food basket’, followed by the Nutrition Environment Measures Survey for Stores (NEMS-S). Comparatively, the Healthy Diets Australian Standardised Affordability and Price (ASAP) instrument supplied data on relative affordability to household incomes. Summary Future research would benefit from a universal instrument reflecting geographic and socio-cultural context and collecting longitudinal data to inform and evaluate initiatives targeting food affordability, availability, and accessibility.

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“…In these two measurements, the characterization of the physical food environment includes different types of food outlets, such as fast-food outlets, supermarkets, grocery stores, etc., which are defined directly as healthy or unhealthy. A recent study evaluated the differences of characteristics from food supplied by different retail food outlets, such as supermarkets, grocery stores, and convenience stores across different types of neighborhoods ( 20 ); thus, we focus on the fast-food outlets in this study.…”

Section: Introductionmentioning

confidence: 99%

An Indicator Measuring the Influence of the Online Public Food Environment: An Analytical Framework and Case Study

et al. 2022

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The online public food environment (OPFE) has had a considerable impact on people's lifestyles over the past decade; however, research on its exposure is sparse. The results of the existing research on the impact of the food environment on human health are inconsistent. In response to the lack of food elements in the definition of the food environment and the lack of a clear method to assess the health attributes and the impact degree of the food environment, we proposed a new analytical framework based on the latest disease burden research, combining the characteristics of China's current food environment, from the perspective of environmental science. We redefined the food environment and proposed that food and its physical space are two core elements of the food environment. Accordingly, we extracted four domains of characteristics to describe the basic components of the food environment. Using the sales records, we designed an approach by referring to the standard process of environmental health indicators, including the health attributes and the impact degree of the food environment, to measure the OPFE of takeaway food outlets. Further, we conducted a case study and extracted three domains of characteristics for more than 18,000 effective takeaway meals from 812 takeaway food outlets located in 10 administrative subdivisions in the Haidian District and Xicheng District of Beijing Municipality. The results showed that more than 60% of single meals sold by takeaway food outlets were considered as healthy, and only 15% of takeaway food outlets sold healthy meals exclusively. Additionally, there were significant differences in health effects among different types of food environments, and high-risk areas of different types of food environments can be spatially identified. Compared with the counting method in the availability of food environment, the proposed new approach can depict food environment characteristics not only in the macro-scale like the counting method but also in the meal-scale. The indicators could be useful for large-scale and long-term monitoring of food environmental changes due to their simple calculation and design depending on the food delivery platform.

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Evaluating Consumer Nutrition Environment in Food Deserts and Food Swamps

Cited by 23 publications

References 31 publications

Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities

Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities

Assessing the Cost of Healthy and Unhealthy Diets: A Systematic Review of Methods

An Indicator Measuring the Influence of the Online Public Food Environment: An Analytical Framework and Case Study

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