Food Costs Are Higher in Counties With Poor Health Rankings

Abstract

Background: Poor dietary habits are associated with higher rates of cardiovascular disease. However, the cost of foods associated with lower risk of cardiovascular disease can be a significant barrier to healthy eating. Objective: The aim of this study is to determine whether food prices per serving differed across Kentucky counties based on health ranking and overall nutritional quality. Methods: Fifteen counties were randomly selected based on County Health Ranking. Overall Nutritional Quality Index and cost of 75 foods were assessed in all 15 counties in the same week. A generalized estimating equations model and post hoc analyses were used to assess differences in food cost by nutritional quality and health ranking. Results: Food prices were significantly less in the most healthy counties compared with the least healthy (Z = 3.8; P < .001; $0.08 per serving). Prices were also significantly higher in least healthy counties (tertile 3) compared with moderately healthy counties (tertile 2) (Z = 2.3; P = .024; $0.05 per serving). Conclusions: Disproportionately higher food costs are associated with poor health outcomes in Kentucky counties. Community-based interventions can potentially improve access to affordable healthy foods. Current supplemental nutritional policies do not address disparate food costs. Health professionals should advocate for policy changes that are reflective of these food cost disparities.

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

“…with four of these studies supplementing the data with online supermarket prices [62][63][64]81]. Additionally, three instruments compared the cost of a 'healthy diet' to either an 'unhealthy or currently consumed diet' [20,88,110], 13 instruments compared the cost of 'healthy' and 'unhealthy' individual foods or product categories [19,38,51,62,63,66,83,87,89,90,103], and 14 instruments did not present a comparison [37,40,46,49,50,52,64,67,70,80,81,91,92,104,105]. 'Current' diets were defined using national survey data [20,110].…”

“…'Current' diets were defined using national survey data [20,110]. Level of healthiness was defined using various benchmarks, namely the NOVA food processing classification system [38], nutrient composition and energy density [38,51,62,63,66,80,83,90], national Dietary Guidelines [19,43,70,[87][88][89][90], and the Dietary Approaches to Stop Hypertension (DASH) dietary pattern [43]. Food affordability was benchmarked using household income [20, 49, 50, 90-92, 103, 105, 110], government subsidies [37,40,87,89,91], and minimum wage [38,66,70]; however, most studies (n = 13) did not determine relative affordability in their analysis [43, 51, 52, 55, 62-64, 67, 73, 80, 81, 83, 88].…”

“…112, 114-117, 119, 121, 124-126] Mixed urban/rural[19, 32, 37, 40, 50, 52, 61, 73, 81, 83-85, 88, 94, 96, 97, 110, 111, 113, 123, 127] Rural[9-11, 56, 78, 82, 87, 90, 91, 103, 106, 109] Not specified[34,35,49,51,74,93,100,101,107,120,122] Study design Cross-sectional [9-11, 20, 32, 35, 36, 39, 40, 42-47, 49, 51-57, 59, 60, 62, 64, 67-73, 75-79, 81, 82, 84-89, 91, 92, 94-96, 99-110, 112-117, 119-122, 124, 125] Longitudinal [19, 33, 34, 37, 38, 41, 48, 50, 58, 61, 63, 65, 66, 74, 80, 83, 90, 93, 97, 98, 111, 123, 127] Data sources Instore price audit [9-11, 19, 20, 32, 33, 36, 38, 39, 42-44, 46-52, 54-57, 59, 60, 66-73, 75, 77, 79, 80, 83, 85-93, 98, 102-110, 112, 114, 115, 119-121, 124]Electronic point of sale data[34,37,40,41,45,61,74,76,78,82,94,96,97,111,126,127] Online price audit[35, 53, 58, 65, 95, 99-101, 116, 123] Instore and online price audits[62-64, 81, 84, 113, 117, 122, 125] No. of food retail outlets One[53,55,58,95,99,116] Between 2 and 10[11, 20, 62-65, 72, 74, 75, 79, 84, 103, 105, 113, 117, 119-125] Between 11 and 20[10,38,46,51,66,70,71,82,…”

Appalachian Bariatric Surgery Population Descriptive Analysis, Surgical Outcomes, and Food Accessibility

“…One study of West Virginia census data found that total number of food stores, business establishments, and mean travel time to work increased rates of obesity among the population [83]. The limited food access in these areas are in part due to rural locality, lower income in the state and lack of vehicle access [74,83,145,[167][168][169]. As dietary change is a common recommendation for weight loss, for those in a health disparate population with limited access to food, following a prescribed or suggested dietary pattern for health purposes may be difficult to achieve and near impossible to sustain [170].…”