Ultra-processed foods, dietary diversity and micronutrient intakes in the Australian population

Abstract

Purpose This cross-sectional study aimed to assess the association between ultra-processed foods consumption and dietary diversity and micronutrient intake in Australia. Methods As part of the Nutrition and Physical Activity Survey (2011–2012), 12,153 participants aged 2 years and above were recruited and interviewed. Dietary intake data were collected by two 24-h dietary recalls using the Automated Multiple-Pass Method. The NOVA classification system was used to group the food items based on the extent and purpose of industrial food processing. The mean micronutrient contents were calculated for the total diet, and for two diet fractions; one made up entirely of ultra-processed foods (NOVA group 4) and the other consisting of all non-ultra-processed foods (aggregation of NOVA food groups 1 to 3). The mean micronutrient content in the ultra-processed and non-ultra-processed food diet fractions were compared. Dietary diversity was measured using the ten Food Group Indicators (FGI) of the Food and Agriculture Organization and was defined as the sum number of FGIs per individual. Multiple linear regression models were used to assess the association between the quintiles of energy contribution of ultra-processed foods, dietary diversity, and micronutrient intake. Results A negative association was found between quintiles of energy contribution of ultra-processed foods and dietary diversity (β = − 0.43; p < 0.001). The overall micronutrient content was lower in the diet fraction dominated by ultra-processed foods compared to the non-ultra-processed food diet fraction in the study population. The dietary contents of vitamins A, E, C, B9, B12, zinc, calcium, iron, magnesium, potassium, and phosphorus were reduced significantly with increased consumption of ultra-processed foods, even after adjustment for sociodemographic factors and dietary diversity. Conclusion The quintiles of energy contribution of ultra-processed foods were negatively associated with dietary diversity and micronutrient intake in Australia.

Ultra-Processed Foods: A Narrative Review of the Impact on the Human Gut Microbiome and Variations in Classification Methods

“…Of the studies in Table 3 , eight used FFQs [ 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 ], seven used 24 h dietary recalls [ 77 , 79 , 80 , 89 , 90 , 91 , 92 ], and two used a combination of methods (FFQs and food records) [ 76 , 78 ] to collect food information. Each of these methods have been validated for use in dietary research, but limitations exist that make food processing classification difficult in some cases.…”

“…Each of these methods have been validated for use in dietary research, but limitations exist that make food processing classification difficult in some cases. When there was ambiguity in the classification of foods, studies resolved these items by several methods: group discussion and consensus [ 83 , 86 , 90 , 91 , 92 ], discussion and defaulting to a lower level of processing [ 77 , 81 , 82 , 85 , 86 , 88 , 89 ], expanding discussion to an external group [ 87 ], and utilizing external resources such as grocery store labels [ 84 , 87 , 90 , 91 ]. As shown, some studies used a combination of these methods, while others did not describe how they worked to resolve discrepancies.…”

“…A third group had two evaluators classify all foods from 24 h dietary recall data; then, a second set of two researchers verified the classifications. Decisions were made utilizing lists of ingredients from food packaging or company websites and discussion went on until consensus was reached [ 90 ]. These difficult cases highlight the lack of consensus on the application of the NOVA system.…”

“… Cordova et al assumed bakery breads from Italy and the UK to be NOVA 3 and commercial packaged bread to be NOVA 4 [ 76 ]. Houshialsadat et al categorized commercial white bread as NOVA 4, while other breads were NOVA 3 [ 90 ]. Kityo et al categorized most loaf bread (‘ sikppang ’) as NOVA 4 [ 84 ].…”

“…In addition to physical health effects, high UPF consumption was associated with an increased risk of depression and psychological distress [85,87]. Interestingly, high UPF consumption has been associated with inadequate consumption of several micronutrients [83,90], which may partially explain some of the adverse health effects associated with UPFs. Food items were classified according to the NOVA system manually using primarily the "Food Description" variable within the ASA24.…”