Structural Analysis of the Relationship of Food Insufficiency to Disease Risk and Outcomes Among Adults From NHANES III

Year: 2001

Research Center: Southern Rural Development Center, Mississippi State University

Investigator: Connell, Carol L., Kathy Yadrick, James T. Johnson, and L. Joseph Su

Institution: University of Southern Mississippi

Project Contact:
Carol L. Connell, Research Coordinator
University of Southern Mississippi
Delta Nutrition Intervention Research Initiative
Box 5054
Hattiesburg, MS 39406-5054


This study was based on the conceptual framework developed by Campbell for risk factors and consequences of food insufficiency. In this framework, food insufficiency could be both an outcome and a predictor of other outcomes, such as poor health. Over the past decade, research has provided evidence for the relationship between food insufficiency and each health risk factor or health outcome proposed by Campbell, but has not demonstrated inter-relationships among all model components simultaneously. The southern region of the United States has a relatively high rate of cardiovascular disease (CVD) and a high rate of food insufficiency. These conditions indicate a need to investigate interrelationships among food insufficiency, diet quality, health behaviors, CVD risk factors, and CVD. Therefore, this study developed and tested a model—derived from Campbell’s conceptual framework— of the relationships among food insufficiency, diet quality, CVD risks, and CVD in the South.

The authors examined these relationships among a sample of adults from the South who participated in the Third National Health and Nutrition Examination Survey (NHANES III). The study examined the relationship between food insufficiency and three categories of individual characteristics, referred to as latent constructs. The latent constructs were (1) health behaviors, (2) CVD risks, and (3) CVD outcomes. The structural model included independent variables for food insufficiency and diet quality, as well as sociodemographic variables known to be associated with food insufficiency and diet quality. Data analysis involved the use of structural equation modeling (SEM) in a two-phase process. In the first phase, the authors estimated the relationships between predictor variables and the latent constructs. In the second phase, the authors tested the structural model using SEM. This involved estimating relationships among latent constructs and predictor variables simultaneously.

The results of the analysis indicated that food insufficiency is more prevalent among individuals with low income and education levels and those who are non- White and female. Evaluation of the measurement models indicated reasonably good fit of the latent constructs and their indicator variables. However, structural equation modeling did not confirm a statistically significant relationship between food insufficiency and CVD. The authors noted that because food insufficiency is correlated with many other factors, it is difficult to disentangle its effect on CVD. They suggest that future research focus on assessing correlations among the indicator variables to better define future structural models of the relationships among food insufficiency and cardiovascular disease risks and outcomes. In addition, the authors suggest that future research assess direct and indirect effects of the indicators for cardiovascular disease. Assessment of these effects may suggest areas of future investigation in cardiovascular disease prevention and management.