High ultra-processed food consumption tied to rising BMI and fat mass in young children

In a recent study published in BMC Medicine, researchers determined the relationship between ultra-processed food (UPF) intake, obesity, and metabolic indicators among preschool children in Chile.

Study: The consumption of ultra-processed foods was associated with adiposity, but not with metabolic indicators in a prospective cohort study of Chilean preschool children. Image Credit: Rimma Bondarenko/Shutterstock.comStudy: The consumption of ultra-processed foods was associated with adiposity, but not with metabolic indicators in a prospective cohort study of Chilean preschool children. Image Credit: Rimma Bondarenko/Shutterstock.com

Background

Childhood obesity has become a growing public health problem globally. Childhood obesity persists throughout time and is related to metabolic abnormalities that appear at a younger age. UPF intake is associated with health disorders such as obesity, particularly in adults.

However, research on pediatric metabolic outcomes is scarce and inconsistent. Given the population health cost of inadequate nutrition among children and exponential increases in UPF consumption, knowing its consequences on metabolic risk variables is critical.

About the study

In the present prospective cohort study, researchers investigated the influence of UPF on obesity and metabolic outcomes among preschoolers in Chile after two years.

The researchers analyzed data from 962 pediatric participants of the Food and Environment Chilean Cohort (FECHIC) study. They collected dietary data in 2016 from four-year-olds with 24-hour recalls. Recall data was collected using the United States Department of Agriculture's (USDA) multiple-pass technique.

The team excluded records with extreme UPF consumption. Mothers were the primary respondents, reporting one day of children's food intake during in-person interviews. Children attended the interviews and provided additional information about eating periods in the absence of respondents (for example, during school hours).

Researchers used the NOVA classification to categorize foods and the Multiple Source Method (MSM) to estimate the consumption of ultra-processed foods in grams and calories.

The first group comprised natural foods and minimally processed ones; the second group comprised processed culinary ingredients; the third group comprised processed foods; and the fourth group comprised UPF.

The team measured adiposity and metabolic indicators in 2018 at six years of age. Adiposity indicators included waist circumference, fat mass in percent and kilograms, and body mass index (BMI) z-scores.

Metabolic indicators were insulin, fasting blood glucose, homeostatic model to assess insulin resistance (HOMA-IR), low-density cholesterol (LDL-c), high-density cholesterol (HDL-c), triglycerides, and total cholesterol.

Researchers estimated the energy requirements using the Dietary Reference Intake (DRI) equation. Linear regressions adjusted for covariates and total calorie intake determined the relationship between UPF intake and study outcomes.

The regressions included inverse probability weighting, accounting for loss to follow-up. Study covariates included age, sex, BM z-scores, television time for children, and maternal factors such as BMI, age, education, work outside the home, and socioeconomic status.

Directed acyclic graphs (DAGs) represented causal networks that linked exposure and study outcomes. The team resolved food categorization disagreements by consensus, and a third dietician independently categorized a subset of the data to confirm the interrater agreement.

Results and discussion

At FECHIC study initiation, the mean age of children was five years, 52% were female, and the mean z-score for BMI was 1.0. The mothers were aged 31 years, and 55% had attained medium-level education. 

After two years, the mean fat mass was 24%, and the mean fasting glucose was 82 mg/dL.

Regular UPF intake accounted for 48% of the calorie intake and 39.0% of total foods in grams at four years. UPF accounted for most calories in children's diets, whereas minimally processed foods contributed the most grams (57%).

The adjusted models showed positive associations between UPF intake and BMI, waist circumference, log-fat body mass, and log-percent fat mass but no relationship with metabolic markers.

The sensitivity analyses using models without the stabilized inverse probability of censuring weights and considering UPF intake in quartiles yielded similar results.

The proportional contribution of UPF to the diet is more significant than the total amount, and the health improvements reported result from a shift away from conventional eating patterns.

UPFs are associated with detrimental health impacts due to their poor nutritional profile, high added sugar and saturated fat concentration, and low vitamin and mineral content.

UPF production frequently uses refined ingredients, resulting in decreased satiety and increased glycemic response. UPFs also have a high energy density and low water content, allowing them to be consumed rapidly in terms of volume and calories, which promotes excessive consumption.

Their reduced protein density may lead to excessive eating of other meals. Widespread UPF consumption may also increase the ingestion of rare or absent chemicals, like food additives.

Conclusion

The study findings showed that UPF consumption was related to obesity in Chilean preschoolers after two years but not metabolic consequences. Longer follow-ups may help understand the history of ultra-processed food use and associated hazards.

Health authorities and policymakers should strengthen global measures to create environments that encourage minimally processed diets while restricting children's access to UPF meals.

Journal reference:
Pooja Toshniwal Paharia

Written by

Pooja Toshniwal Paharia

Pooja Toshniwal Paharia is an oral and maxillofacial physician and radiologist based in Pune, India. Her academic background is in Oral Medicine and Radiology. She has extensive experience in research and evidence-based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.

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