Ultra-processed food consumption and risk of obesity: a prospective cohort study of UK Biobank

Ultra-processed foods, as defined by the NOVA food classification system, are industrial formulations of substances derived from foods, which typically contain cosmetic additives (i.e. flavours and colours) and little, if any, whole foods [1]. Some examples of ultra-processed foods are soft drinks, flavoured dairy drinks, sweet or savoury packaged snacks, confectionery, breakfast cereals, packaged breads and buns, reconstituted meat products and pre-prepared frozen or shelf-stable dishes. These formulations are extremely palatable, convenient, often sold in large portion sizes, and aggressively marketed [2, 3]. The growing production and consumption of ultra-processed products has gradually replaced the traditional food systems and dietary patterns based on minimally processed foods and freshly prepared meals [3, 4]. In a recent global analysis of the trends in sales of ultra-processed foods, the UK has been ranked the third highest consumer of ultra-processed foods (140.7 kg/capita/year) among 80 high- and middle-income countries studied [5].

A growing body of evidence has suggested that the consumption of ultra-processed foods increases the risk of obesity. Analyses of nationally representative dietary surveys conducted in various countries, including the UK, have consistently shown a strong association between consumption of ultra-processed foods and obesogenic dietary nutrient profiles [6‐10]. Recent population-based cross-sectional studies have demonstrated a positive association between the consumption of ultra-processed foods and obesity in Brazil [11], the United States [12] and Canada [13]. Furthermore, a two-week, cross-over, randomized controlled trial of 20 weight-stable adults found that higher consumption of ultra-processed foods led to increased energy intake and a substantial gain in body weight and fat mass [14].

There has been limited assessment of the associations between ultra-processed food consumption and obesity using data from prospective cohort studies. A study of 8451 university graduates in Spain found that higher consumption of ultra-processed food was associated with higher risk of developing overweight and obesity within 9 years of follow-up [15]. Another prospective cohort study of 11,827 Brazilian civil servants has found that during an approximately four-year follow-up time, greater ultra-processed food consumption led to larger increases in body mass index (BMI) and waist circumference (WC) [16]. Both studies used food frequency questionnaires to assess dietary intake rather than 24-h recall, that are better at capturing a wider range of foods and beverages consumed, especially those from ultra-processed foods, thus may provide a more precise dietary information. The present study adds to the existing literature by investigating the associations between ultra-processed food consumption and a wider range of obesity indicators—overall and abdominal obesity, changes in BMI, WC and % of body fat—using 24-h dietary recall data as our exposure in a cohort of UK adults.

A total of 22,659 participants (52.1% women and 47.9% men) were included in the present study. The analyses of obesity and abdominal obesity incidence were based on 18,218 and 17,113 participants without obesity and abdominal obesity at baseline, respectively. Participants excluded due to missing anthropometric data were similar to those included in this study (Supplementary table S1). The mean baseline age of participants was 55.9 (SD 7.4) years. Table 1 shows the baseline characteristics of participants according to quartiles of the proportion of ultra-processed foods in the diet. Compared with the first quartile (lowest consumption), participants in the highest quartile of ultra-processed foods intake were younger, were more likely to live in the most deprived area and had never smoked, had lower physical activity levels and had higher mean BMI and WC.

The mean contribution of ultra-processed foods to the overall diet (in % of total energy) was 48.6% (SD 18.0) (Supplementary table S2). Briefly, the main food groups contributing to ultra-processed food intake were snacks and desserts (33%, for example, pastries, buns, cakes, biscuits, confectionary, packaged salty snacks and industrial desserts) followed by ultra-processed bread (21%, for example, bagel, burger bun, bread roll and bap), frozen and shelf-stable ready-to-eat/heat meals (16%, for example, industrial chips/French fries, sausage, nuggets, fish fingers and other reconstituted meat products, industrial pizza and packaged pre-prepared meals), beverages (15%, for example, milk-based drinks, soft and fruit drinks, fruit juices, alcoholic drinks and coffee drinks), spreads, sauces and other ultra-processed foods (9%, margarine and other spreads, sauces, dressing and gravies, chocolate/nut spread, spreadable cheese, sweeteners and meat alternative), and breakfast cereals (6%, for example, sweetened cornflake and sweetened oat crunch type cereal) (Fig. 2). Baseline characteristics of the study population included in incidence analysis according to quartiles of consumption of ultra-processed foods are presented in Supplementary table S3. No statistically significant interaction was identified between the dietary contribution of ultra-processed foods and the covariates tested.

The associations between dietary contribution of ultra-processed foods (% of total energy) and indicators of obesity are shown in Table 2. The linearity assumption between intake of ultra-processed food and risks of obesity, abdominal obesity, ≥ 5% increase in BMI, ≥ 5% increase in WC and ≥ 5% increase in BF were assessed using restricted cubic spline (respective p values were 0.59, 0.27, 0.03, 0.08 and 0.22) (Supplementary figure S1). No statistically significant violation from the linearity assumption was observed except for the risk of ≥ 5% increase in BMI which showed significance against the null hypothesis (at α = 0.05); therefore, we consider the linear relationship as the best approximation for the continuous association between levels of ultra-processed food consumption and risk of each health outcome. A total of 947 cases of obesity and 1900 cases of abdominal obesity were identified during follow-up (97,090 and 91,380 person-years, respectively). After adjustment for potential confounders, participants in the highest quartile of ultra-processed food consumption presented a 79% and 30% relatively higher risk of developing obesity (adjusted HR 1.79; 95% CI 1.06–3.03) and abdominal obesity (adjusted HR 1.30; 95% CI 1.14–1.48), respectively, than those in the lowest quartile of consumption. A 10% increase in the consumption of ultra-processed foods was associated with increased risk of abdominal obesity (adjusted HR 1.06; 95% CI 1.03–1.08), while association for overall obesity was not statistically significant (adjusted HR 1.10; 95% CI 0.99–1.22).

We identified 3871, 5981 and 3340 participants who had a greater than 5% increase in BMI, WC and body fat, respectively (during 119,108, 121,067 and 17,660 person-years of follow-up). After adjustment for potential confounders, participants in the highest quartile of ultra-processed food consumption had significantly higher risk of having a ≥ 5% increase in BMI (adjusted HR 1.31; 95% CI 1.20–1.43), WC (adjusted HR 1.35; 95% CI 1.25–1.45) and body fat (adjusted HR 1.14; 95% CI 1.03–1.25) than those in the lowest quartile of consumption. A significant dose–response relation was observed for all the obesity indicators (p for linear trend across quartile < 0.05), except for the incidence of obesity when the model was adjusted for BMI at baseline (p for linear trend = 0.068). A 10% increase in the consumption of ultra-processed foods was associated with increased risk of having a ≥ 5% increase in WC (adjusted HR 1.06; 95% CI 1.05–1.08) and body fat (adjusted HR 1.03; 95% CI 1.01–1.05).

The analyses of the association between dietary contribution of ultra-processed food (% of total energy) and indicators of obesity stratified by BMI status at baseline are shown in Table 3. Associations observed among participants who were normal weight or overweight at baseline were similar to those seen for the whole population in the case of a 5% increase in BMI and WC, while no statistically significant association was observed for a 5% increase in the percentage of body fat. For participants who had obesity at baseline, the associations between dietary contribution of ultra-processed food (sex-specific quartile and continuous) and risk of having a ≥ 5% increase in WC and body fat became stronger, while no statistically significant association was observed for a 5% increase in BMI.

In the sensitivity analyses, the associations between dietary contribution of ultra-processed food and indicators of obesity were similar after excluding individuals who were on low calorie diet (Supplementary tables S4 and S5). Broadly similar estimates were also found with models using average annual household income instead of IMD score (Supplementary tables S6 and S7).

Findings from this prospective cohort study of British adults show that diets rich in ultra-processed foods were associated with an 79% and 30% significant increase in the risk of obesity and abdominal obesity, respectively. Moreover, higher consumption of ultra-processed foods also increased the risk of a gain in BMI, WC and body fat of 5% or more during the follow-up period (median of 5.6 years). In general, stratification by BMI status at baseline confirmed the findings in the whole population.

Our results corroborate findings from large, population-based cross-sectional studies that identified significant, dose–response associations between higher consumption of ultra-processed foods and obesity [13]. A cohort study of university alumni in Spain confirmed this association by showing a 26% increased risk of developing obesity in the highest quartile of ultra-processed food consumption compared to the lowest quartile [15]. Similarly, a prospective study conducted with Brazilian adults found an approximately 20–30% greater risk of large weight and waist circumference gains in the highest quartile of ultra-processed food consumption compared to the lowest quartile [16].

Several mechanisms may explain the relationship between ultra-processed foods consumption and obesity. Positive associations between ultra-processed foods consumption and the dietary nutrient profiles known to increase the risk of obesity, and other diet-related chronic diseases, are well established in the UK [6, 27] as well as in other middle- and high-income countries [7‐10]. A recent 2-week, cross-over, randomized controlled trial of 20 weight-stable healthy adults have shown that, compared to a diet with no ultra-processed foods, consuming a diet high in ultra-processed foods resulted in increases in dietary energy intake as well as substantial body weight and fat gain, even when the ‘ultra-processed diet’ offered to participants was closely matched to the control diet in calories, sugar, fat, sodium, fibre and macronutrients [14]. These findings suggest that characteristics of ultra-processed foods other than their nutrient profile may also be obesogenic. In this same trial, the authors have also found changes in hormone levels, such as appetite-suppressing hormone PYY and hunger hormone ghrelin, and an increase in the eating rate during the ultra-processed diet [14]. In a more recent study based on pooled data from five previously published reports of food energy intake rates, ultra-processed foods had an energy intake rate twice as high as that observed among unprocessed foods (69.4 and 35.5 kcal/min, respectively) [28]. This can be explained by the oro-sensory properties of the ultra-processed foods (e.g. softer food) that make them easier to chew and swallow.

Other potential mechanisms for the link between ultra-processed diets and obesity may be related to the low satiety potential and induction of high glycaemic responses [29] of ultra-processed foods or the little or no presence of intact food matrix in these products which causes changes in the composition and metabolic behaviour of the gut microbiota that promote obesity and other inflammatory diseases [30, 31]. Cosmetic additives, commonly used in the manufacture of ultra-processed foods, could also be part of the mechanisms linking them to obesity. For instance, monosodium glutamate, a flavour enhancer used in several ultra-processed foods, may contribute to obesity by its potential endocrine disrupting effect [32]. Carboxymethylcellulose and polysorbate-80, two emulsifiers that are also commonly present in ultra-processed foods, were shown to induce low-grade inflammation and obesity in mice [33]. In addition, artificial sweetener may contribute to obesity by modulating the gut microbiota [36] and stimulating basal insulin secretion [37]. Finally, ultra-processed foods are typically wrapped in plastic packages, and several plasticizers, such as bisphenol A, have been found associated with obesity [38, 39].

Our study has several strengths. We used data from the UK Biobank, which is a prospective cohort with detailed dietary data collected through a previously validated 24-h recall questionnaire. Of note, the two other cohort studies [15, 16] were based on data collected from food frequency questionnaires, that are less detailed and possibly less accurate for the purpose of categorizing ultra-processed ad non-ultra-processed foods. Another strength is the availability of several measures of adiposity which were objectively measured by trained staff and were not based on self-report. Self-reported data tend to underestimate adiposity, especially among obese women [40]. In addition, we used the NOVA food classification system to classify foods by their level of processing using standardized and objective criteria.

Potential limitations should be considered. First, our study included volunteered subjects who were older and less likely to be obese (18% in our sample vs 29% in British population) than the general population in the UK [41]. They also had higher intakes of unprocessed or minimally processed foods (especially fruit, vegetables and fish) and lower intakes of ultra-processed foods than the British population [6]. Thus, we may have underestimated the association between ultra-processed food consumption and obesity due to a lower contrast between the extreme quartiles of ultra-processed food consumption. Second, a high number of participants were lost to follow-up in this study. Although ultra-processed food consumption was similar between those with and without follow-up data (48.6% and 48.5%, respectively, p = 0.260), we cannot preclude the possibility that the relationship between ultra-processed consumption and incidence of overall obesity and abdominal obesity may have differed between groups. Third, a key limitation of the dietary assessment method is underreporting of some foods (particularly unhealthy foods), though 24-h recall questionnaires are recognized to be one of the most comprehensive methods for assessing dietary intake. Previous studies suggest that individuals with obesity may underreport consumption of foods with caloric sweeteners [42], such as desserts and sweet baked goods [43, 44]. This social desirability bias may lead to underestimation of the dietary contribution of ultra-processed foods or dilution of the association between ultra-processed food consumption and adiposity. Nevertheless, accuracy of the dietary intake was improved by online administration of the dietary questionnaire, which is expected to minimize any reporting bias due to social desirability. Moreover, we excluded extreme values of total calorie intake from the analysis. Fourth, the estimation of ultra-processed food consumption based on one 24-h recall as opposed to an averaged intake over multiple days is a limitation. However, due to the inconsistencies in the timing of anthropometric measurements and the administrations of 24-h recalls, we considered the first completed 24-h recall as the best representation of participants’ dietary intake at baseline. Fifth, the Biobank collects limited information indicative of food processing (for example, product brands), which may lead to misclassification of some food items. This bias is more likely to occur in foods, such as pizza, where there is insufficient information available for classification purposes. In such cases, the most frequently consumed alternative (culinary preparation or manufactured product) was chosen. If both options were common, we selected the option with lower level of processing. Potential misclassification would, therefore, lead to an underestimation rather than a spurious exaggeration of ultra-processed food consumption. Sixth, the exact date of the development of the outcomes is not known because the Biobank did not have more frequent measurements. Therefore, we used the date of measurement as an approximation of the date of the event. Finally, due to the observational nature of our study, residual confounding cannot be completely ruled out although we accounted for a wide range of confounders in our statistical models.

Given the endemic presence of ultra-processed foods in the UK (where they contribute to 57% of total calories intake [6]) and globally [5], the analyses presented here suggest that actions to reduce the consumption of ultra-processed foods could produce important public health benefits. Brazil, Uruguay, Ecuador and Peru have already included the avoidance of ultra-processed foods in their food-based dietary guidelines [45‐48]. Recently, France has set a goal of 20% reduction in consumption of ultra-processed foods by 2022 [49]. Mexico introduced taxes on common ultra-processed foods, such as sugar-sweetened beverages and high-energy dense snacks, and studies already demonstrated a significant decline in the purchases of those products [50, 51]. In 2016, Chile implemented a law on compulsory warning labels and advertising restrictions for foods/beverages high in at least one critical nutrient, including energy, sugars, saturated fats and sodium, and a recent study has already shown a positive influence of the Chilean law on people’s consumer behaviours [52]. Other ways that governments might intervene to promote freshly prepared meals include subsidies for fresh or minimally processed foods and tax breaks for local food co-operatives and food growers to ensure that healthy foods are affordable and available to all. Ultimately, actions that promote healthy choices of foods and benefits of cooking are the key drivers to improve population health [53].

This study adds valuable evidence to the literature showing strong associations between ultra-processed food consumption and several measures of adiposity. These findings suggest that policy actions to achieve necessary reductions in ultra-processed food consumption should be considered, such as through adequate food labelling, restrictions on advertising and promotion of these products and fiscal policies that make fresh foods and fresh dishes and meals more affordable than ultra-processed foods. In addition, dietary guidelines for the UK population should be reviewed to take food processing into account.