Ultra-processed food consumption and obesity in the Australian adult population

Non-communicable diseases (NCDs) are a leading cause of death in Australia, with obesity being a significant risk factor. Australia has experienced a dramatic rise in obesity prevalence over the past two decades, ranking among the highest rates in OECD countries. This increase coincides with a rise in ultra-processed food consumption. Ultra-processed foods, defined by the NOVA classification system, are industrial formulations made from substances derived from foods, often with added flavors, colors, and other additives. These foods are often nutritionally unbalanced, hyper-palatable, and convenient. Previous research suggests a link between ultra-processed food consumption and weight gain, obesity, and other NCDs. This study uses data from the Australian National Nutrition and Physical Activity Survey (NNPAS) to examine the association between ultra-processed food consumption and obesity in the Australian adult population, considering age, sex, and physical activity levels. The study aims to determine if increased consumption of ultra-processed foods correlates with a greater prevalence of obesity, independent of other factors. This research is crucial for understanding and addressing the growing obesity epidemic in Australia and informing public health interventions. The increase in global obesity rates is linked to changes in global food systems, which are increasingly dominated by ultra-processed foods. A randomized controlled trial (RCT) even showed that a diet high in ultra-processed foods led to significant weight gain compared to a diet without ultra-processed foods, even when macronutrients were matched, suggesting that mechanisms beyond simple nutrient content play a role. A previous study using the same NNPAS data found associations between ultra-processed food consumption and intakes of nutrients outside levels recommended for obesity prevention, providing a foundation for this study.

A substantial body of research globally has established a link between ultra-processed food consumption and obesity. Cross-sectional and longitudinal studies across various populations, including Brazil, Spain, the U.S., Canada, and the U.K., consistently demonstrate this association. Studies have shown that higher consumption of ultra-processed foods is linked to weight gain, increased risk of obesity, and other NCDs. Ecological studies have also found correlations between national availability of ultra-processed foods and obesity prevalence. The NOVA classification system, used in this study, is gaining international recognition as a valuable tool for understanding the relationship between food processing, diet quality, and health outcomes. While the exact mechanisms are still under investigation, the poor nutrient profile of ultra-processed foods, along with non-nutritional factors related to processing techniques and their convenience, contribute to the problem. The displacement of traditional, healthier dietary patterns by ultra-processed foods also plays a significant role. Many studies reveal the negative impact of ultra-processed food consumption on nutrient intake, leading to deficiencies in essential nutrients while increasing the intake of sugar, unhealthy fats, and salt.

This cross-sectional study utilized data from the 2011–2012 Australian National Nutrition and Physical Activity Survey (NNPAS). The NNPAS employed a complex, stratified, multistage probability cluster sampling design to obtain a nationally representative sample of the Australian population. The study included 9519 households with 12,153 participants interviewed. Dietary data was collected using two non-consecutive 24-hour dietary recalls (one face-to-face, one by telephone). Food items were classified using the NOVA classification system into four groups: unprocessed or minimally processed, processed culinary ingredients, processed foods, and ultra-processed foods. Anthropometric measurements (weight, height, waist circumference) were also obtained to calculate BMI and assess obesity and abdominal obesity. The analytical sample was restricted to adults aged 20–85 years with complete data on BMI and waist circumference. Exclusions were made for pregnant and lactating women, those with implausible energy intakes, and participants with missing data on outcomes. The final analytic sample consisted of 7411 participants. Data analysis involved stratifying participants into quintiles based on the dietary share of ultra-processed foods (percentage of total energy intake). Characteristics of participants across quintiles were compared using Pearson's χ² test and linear regression. Linear and logistic regression analyses examined the association between ultra-processed food consumption (quintiles) and obesity indicators (BMI, waist circumference, obesity, and abdominal obesity). Models were adjusted for socio-demographic variables, physical activity, and smoking status. Subgroup analyses were performed by age, sex, and physical activity level. Sensitivity analyses excluded participants with extreme BMI values, those on special diets, and those with diagnoses of diet-related chronic diseases to address potential reverse causality. Weighted analyses were conducted to account for the complex sampling design and allow for population-level inferences. Ethical approval was obtained before commencing the analysis.

The study found significant (P-trend ≤ 0.001) direct dose-response associations between the dietary share of ultra-processed foods and all obesity indicators after adjustment for covariates. Individuals in the highest quintile of ultra-processed food consumption had significantly higher BMI (0.97 kg/m²; 95% CI 0.42, 1.51) and waist circumference (1.92 cm; 95% CI 0.57, 3.27) compared to those in the lowest quintile. They also had significantly higher odds of obesity (OR = 1.61; 95% CI 1.27, 2.04) and abdominal obesity (OR = 1.38; 95% CI 1.10, 1.72). Subgroup analyses showed that these positive associations persisted across all age groups, sexes, and physical activity levels, although some subgroup associations did not reach statistical significance, particularly in the youngest age group for waist circumference and abdominal obesity. The association between ultra-processed food consumption and obesity was stronger among people aged ≥40 years, women, and inactive individuals. Sensitivity analyses, which accounted for potential reverse causality by excluding individuals with extreme BMI values, those on special diets, or with diagnoses of diet-related chronic diseases, showed an increase in the magnitude of the associations for all obesity indicators in the fifth quintile of ultra-processed food consumption. In essence, Australians whose diets contained over 62% ultra-processed foods had significantly higher BMI and waist circumference, and much higher odds of obesity and abdominal obesity, than those whose diets contained less than 22% ultra-processed foods.

This study provides strong evidence for an association between ultra-processed food consumption and obesity in the Australian adult population. The findings are consistent with a growing body of international research showing a similar link in other high-income countries. The significant dose-response relationship observed strengthens the evidence for a causal link, supported further by the results of previous randomized controlled trials demonstrating weight gain in response to ultra-processed diets. The mechanisms underlying this association likely involve several factors, including the nutritional profile of ultra-processed foods (high in energy density, unhealthy fats, added sugar, and salt; low in fiber and micronutrients), processing techniques that affect satiety and appetite signaling, and the displacement of healthier foods from the diet. The consistency of the association across age, sex, and activity levels indicates a broad impact of ultra-processed food consumption on obesity risk. While reverse causality cannot be entirely ruled out, sensitivity analyses strengthened the findings by adjusting for those potential factors. The study's strength is in its use of nationally representative data. The results have significant implications for public health policy and dietary guidelines in Australia, highlighting the need for interventions that promote healthier food choices and reduce the consumption of ultra-processed foods.

This study confirms a significant association between ultra-processed food consumption and obesity among Australian adults, supporting the growing body of evidence internationally. The findings underscore the importance of considering the role of food processing in obesity prevention strategies. Future research could explore specific mechanisms underlying this relationship, examining effects on gut microbiota, satiety hormones, and other potential pathways. Further investigations into the effectiveness of interventions targeting ultra-processed food consumption are needed to inform effective public health initiatives.

The cross-sectional design of this study prevents the establishment of causality. While biologically plausible and supported by other research, it cannot definitively conclude that ultra-processed food consumption directly causes obesity. Reverse causality cannot be fully excluded, though sensitivity analyses aimed to mitigate this. The reliance on a single 24-hour dietary recall may underrepresent the habitual diet and introduce some error. Despite adjustments for many confounders, residual confounding from unmeasured variables remains a possibility. Some misclassification of foods due to the limitations of the food composition database is also possible.