Knowledge Visualizations to Inform Decision Making for Improving Food Accessibility and Reducing Obesity Rates in the United States
Bibliographic Data
| ID | 15514592 |
|---|---|
| Authors | Raphael D Isokpehi (0000-0002-6877-0840, Bethune-Cookman University, corresponding author), Matilda O Johnson (0000-0002-1451-9984, Bethune-Cookman University), Bryanna Campos (Association of State Public Health Nutritionists), Arianna Sanders (Bethune-Cookman University), Thometta Cozart (0000-0003-1278-8862, Association of State Public Health Nutritionists), Idethia S Harvey (0000-0002-6535-3910, Texas A&M University) |
| Year | 2020 |
| Volume | 17 |
| Issue | 4 |
| Pages | 1263-1263 |
| Publication date | 2020-02-16 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph17041263 |
| PMID | 32079089 |
| OpenAlex | W3005819364 |
| Language | EN |
| Citations received | 2 |
| References cited | 52 |
The aim of this article is to promote the use of knowledge visualization frameworks in the creation and transfer of complex public health knowledge. The accessibility to healthy food items is an example of complex public health knowledge. The United States Department of Agriculture Food Access Research Atlas (FARA) dataset contains 147 variables for 72,864 census tracts and includes 16 food accessibility variables with binary values (0 or 1). Using four-digit and 16-digit binary patterns, we have developed data analytical procedures to group the 72,684 U.S. census tracts into eight and forty groups respectively. This value-added FARA dataset facilitated the design and production of interactive knowledge visualizations that have a collective purpose of knowledge transfer and specific functions including new insights on food accessibility and obesity rates in the United States. The knowledge visualizations of the binary patterns could serve as an integrated explanation and prediction system to help answer why and what-if questions on food accessibility, nutritional inequality and nutrition therapy for diabetic care at varying geographic units. In conclusion, the approach of knowledge visualizations could inform coordinated multi-level decision making for improving food accessibility and reducing chronic diseases in locations defined by patterns of food access measures
Cartography · Census · Data science · Environmental health · Geocoding · Geography · Knowledge management · Knowledge transfer · Population · Public health · Computer Science · Medicine · Nursing · Nutritional Studies and Diet
Food Deserts and the Causes of Nutritional Inequality
Concepts and critical perspectives for food environment research
Public participation in health care priority setting
Rising rural body-mass index is the main driver of the global obesity epidemic in adults
Prevalence of Obesity Among Adults From Rural and Urban Areas of the United States
Obesity among black women in food deserts
Genomic Evidence for Bacterial Determinants Influencing Obesity Development
Food availability and food access in rural agricultural communities
The local food environment and diet
SNAPScapes
Juggling the five dimensions of food access
Food Environments and Obesity
City-Level Measures of Health, Health Determinants, and Equity to Foster Population Health Improvement
Current research in the epidemiology and public health of aging--the need for more diverse strategies
Big Data, Large-Scale Text Analysis, and Public Health Research
Neighborhood Disparities in Access to Healthy Foods and Their Effects on Environmental Justice
Sustainable development goal 2
Examining community and consumer food environments for children
| Citations per year | 0.5 |
|---|---|
| Citation span | 2022 - 2024 (3) |
| Highly cited | No |