A Sex-Specific Analysis of Nutrition Label Use and Health, Douglas County, Nebraska, 2013

Prev Chronic Dis. 2015 Sep 24:12:E158. doi: 10.5888/pcd12.150167.

Abstract

Introduction: In 2014 the US Food and Drug Administration proposed a series of changes to its 1992 guidelines on nutrition facts labeling to help consumers make informed food choices. To date, few studies have examined the association between consumers' use of the nutrition label and health. The objective of this study was to assess the association between nutrition label use and health and to determine whether the association differs by sex.

Methods: Using data from a population-based, random sample survey of 1,503 participants conducted in Nebraska in 2013, we performed χ(2) tests to examine bivariate associations between selected health variables and nutrition label use, followed by logistic regression analysis to estimate these associations in a multivariate framework.

Results: A U-shaped relationship between self-rated health (SRH) and nutrition label use was observed. Both excellent and poor SRH were associated with a higher likelihood of nutrition label use than the 3 SRH categories in between. Being obese or having 1 of 4 chronic conditions (hypertension, diabetes, heart disease, high cholesterol) were both associated with higher odds of nutrition label use (odds ratio [OR] = 2.63, P < .001; OR = 1.71, P < .05, respectively) among men. These associations, however, were not significant among women.

Conclusion: A close association existed between health and nutritional label use. This association was more pronounced among men than among women. Nutrition education may benefit from factoring in the association between health and use of nutrition labels and the differences in these associations by sex.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Body Mass Index
  • Chronic Disease / epidemiology*
  • Chronic Disease / psychology
  • Feeding Behavior / psychology*
  • Female
  • Food Labeling*
  • Health Behavior*
  • Health Services Accessibility / economics
  • Health Services Accessibility / statistics & numerical data
  • Health Status Indicators
  • Humans
  • Insurance Coverage / statistics & numerical data
  • Life Style
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Nebraska / epidemiology
  • Nutrition Policy*
  • Obesity / epidemiology*
  • Population Surveillance
  • Regression Analysis
  • Self Report
  • Sex Factors
  • Socioeconomic Factors
  • Surveys and Questionnaires