Online nutrition information for pregnant women: a content analysis

Matern Child Nutr. 2017 Apr;13(2):e12315. doi: 10.1111/mcn.12315. Epub 2016 Jun 29.

Abstract

Pregnant women actively seek health information online, including nutrition and food-related topics. However, the accuracy and readability of this information have not been evaluated. The aim of this study was to describe and evaluate pregnancy-related food and nutrition information available online. Four search engines were used to search for pregnancy-related nutrition web pages. Content analysis of web pages was performed. Web pages were assessed against the 2013 Australian Dietary Guidelines to assess accuracy. Flesch-Kincaid (F-K), Simple Measure of Gobbledygook (SMOG), Gunning Fog Index (FOG) and Flesch reading ease (FRE) formulas were used to assess readability. Data was analysed descriptively. Spearman's correlation was used to assess the relationship between web page characteristics. Kruskal-Wallis test was used to check for differences among readability and other web page characteristics. A total of 693 web pages were included. Web page types included commercial (n = 340), not-for-profit (n = 113), blogs (n = 112), government (n = 89), personal (n = 36) and educational (n = 3). The accuracy of online nutrition information varied with 39.7% of web pages containing accurate information, 22.8% containing mixed information and 37.5% containing inaccurate information. The average reading grade of all pages analysed measured by F-K, SMOG and FOG was 11.8. The mean FRE was 51.6, a 'fairly difficult to read' score. Only 0.5% of web pages were written at or below grade 6 according to F-K, SMOG and FOG. The findings suggest that accuracy of pregnancy-related nutrition information is a problem on the internet. Web page readability is generally difficult and means that the information may not be accessible to those who cannot read at a sophisticated level. © 2016 John Wiley & Sons Ltd.

Keywords: accuracy; internet; nutrition; online; pregnancy; readability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Australia
  • Data Accuracy*
  • Diet
  • Female
  • Health Knowledge, Attitudes, Practice*
  • Health Literacy*
  • Humans
  • Internet*
  • Nutrition Policy
  • Patient Acceptance of Health Care
  • Pregnancy*
  • Pregnant Women