In the past, researchers looked at the relationship between individual foods and nutrients and health. Today, there is interest in looking at how combinations of foods and beverages, or dietary patterns, impact health. Statistical methods called factor and cluster analyses can be used to describe the patterns of foods and beverages people eat. This summary of a NEL review presents what we know about dietary patterns of certain groups of people described using factor and cluster analysis and the likelihood of developing type 2 diabetes.

Conclusion

Limited and inconsistent evidence from epidemiological studies examining dietary patterns derived using factor or cluster analysis in adults found that consumption of a dietary pattern characterized by vegetables, fruits, whole grains, and reduced-fat dairy products tends to be associated with more favorable body weight status over time than consumption of a dietary pattern characterized by red meat, processed meats, sugar-sweetened foods and drinks, and refined grains.

What the Research Says

• Results from the twelve studies included in this review tell us that dietary patterns high in vegetables, fruits, low-fat dairy products, and whole grains may prevent people from getting type 2 diabetes.

• These studies also show that dietary patterns high in red meat, sugar-sweetened foods and drinks, French fries, refined grains, and high-fat dairy products tend to increase people’s risk of getting type 2 diabetes.

• This review raised some key issues that make it harder to make stronger recommendations:

  • There were many differences in how the studies were done.

  • The dietary patterns differed a lot between studies.

Background

The goal of this systematic review project is to identify patterns of food and beverage intake that promote health and prevent disease. Historically, most dietary guidance has been based on research conducted on individual food components or nutrients. Dietary patterns are defined as the quantities, proportions, variety, or combination of different foods, drinks, and nutrients (when available) in diets, and the frequency with which they are habitually consumed. Factor and cluster analysis allow examination of the relationship between prevailing dietary patterns of a population and outcomes of public health concern. The objective of this systematic review was to assess the relationship between patterns of food and beverage intake identified using factor and cluster analysis, and risk for type 2 diabetes.

Conclusion Statement

Limited and inconsistent evidence from epidemiological studies indicates that in adults, dietary patterns derived using factor or cluster analysis, characterized by vegetables, fruits, and low-fat dairy products tend to have an association with decreased risk of type 2 diabetes, and those patterns characterized by red meat, sugar-sweetened foods and drinks, French fries, refined grains, and high-fat dairy products tended to show an increased association for risk of type 2 diabetes. Among studies, there was substantial variation in food group components and not all studies with similar patterns showed significant association (Grade: III-Limited).

Methods

Literature searches were conducted using PubMed, Embase, Navigator (BIOSIS, CAB Abstracts, and Food Science and Technology Abstracts), and Cochrane databases to identify studies that evaluated the association between dietary patterns defined using factor or cluster analysis and risk of type 2 diabetes. Studies that met the following criteria were included in the review: Human subjects; Ages: 2 years and older; Populations: Healthy and those with elevated chronic disease risk; subjects from countries with high or very high human development (based on the 2011 Human Development Index); randomized controlled trials, non-randomized controlled trials, or quasi-experimental studies; Sample size: Minimum of 30 subjects per study arm; Dropout rate less than 20 percent; Study assesses dietary intake using factor and cluster analysis; study considered type 2 diabetes and risks of type 2 diabetes; published in English in a peer-reviewed journal. The date range for the conduct of studies was unlimited.

The results of each included study were summarized in evidence worksheets (including a study quality rating) and evidence table. A group of subject matter experts were involved in a qualitative synthesis of the body of evidence, development of a conclusion statement, and assessment of the strength of the evidence (grade) using pre-established criteria including evaluation of the quality, quantity, consistency, magnitude of effect, and generalizability of available evidence.

Findings

• Twelve prospective cohort studies examined dietary patterns and their association with T2D incidence. Eleven studies used factor analysis and one used cluster analyses to identify a total of 33 diverse dietary patterns. Studies ranged in size from 690 to 75,512 subjects, were conducted in the United States (five), Japan (two), the Netherlands, Australia, Finland, China, and the United Kingdom, and ranged in duration from 4 to 23 years.
  • Dietary patterns associated with lower risk of T2D were characterized by vegetables, fruits, low-fat dairy, and whole grains and those associated with increased risk of T2D were characterized by red meat, sugar-sweetened foods and drinks, French fries, refined grains, and high-fat dairy products.

• Three prospective cohort studies assessed the association between dietary patterns derived using cluster analysis and factor analysis and plasma glucose levels. Studies ranged in size from 1,146 to 5,824 subjects and were conducted in the United States (two studies) and Denmark.

  • Studies focused on intermediate outcomes were too few and too diverse in methodology to develop a conclusion.

Discussion

The ability to draw strong conclusions was limited due to the following issues:

• Variations in methodology, the number and type of food groupings (e.g., vegetables grouped together or in different groups, regional food groupings), definitions, and naming conventions found in the review make analysis challenging.

• Diet assessment methodology may not accurately capture important elements of the diet. Most longitudinal studies include only baseline measure of dietary intake and do not account for changes in subjects’ diets, availability and variations in the food supply.

• Patterns derived from factor or cluster analysis represent the prevailing dietary patterns of a specific population and are therefore not generalizable and do not represent the optimal diet to protect against disease. However, studies in this review identify characteristics of dietary patterns actually consumed, which are associated with increased and decreased incidence of type 2 diabetes.