Evidence for protein leverage in a general population sample of children and adolescents

Childhood obesity is a significant global health concern, linked to adverse psychosocial and cardiometabolic consequences. Obesity arises from an imbalance between total energy intake (TEI) and total energy expenditure (TEE). Macronutrient appetite systems—for carbohydrates, fats, and proteins—regulate TEI. In balanced food environments, these systems maintain macronutrient targets. However, unbalanced diets, such as those high in ultra-processed foods, can disrupt this balance. The protein leverage hypothesis (PLH) suggests that protein intake is tightly regulated, and reduced dietary protein leads to compensatory overconsumption of energy, increasing obesity risk. While evidence for PLH exists in adults, studies in children and adolescents are limited. This study investigates PLH in a population sample of Finnish children followed from primary school to adolescence, examining the relationship between dietary protein and TEI, and the association between TEI and adiposity measures.

Studies using the nutritional geometry framework have demonstrated stronger regulation of protein intake compared to carbohydrates and fats in animals and adult humans. Reduced protein intake results in energy overconsumption to compensate for protein dilution—a phenomenon called protein leverage (PL). PLH posits that PL drives energy overconsumption and obesity risk in ecological settings. Although PL and PLH are established in adults, research in children and adolescents is limited to a single cross-sectional study on a severely obese Australian cohort. This study aims to fill this gap by investigating PL and its association with adiposity in a general population sample of Finnish children and adolescents.

This study utilizes data from the PANIC study, an 8-year controlled trial investigating the effects of a combined physical activity and dietary intervention on health outcomes in Finnish children. Data were collected at three time points: baseline (TO, ages 6-8 years), 2-year follow-up (T1), and 8-year follow-up (T2). Body size, body composition (using dual-energy X-ray absorptiometry, DXA), and pubertal stage were assessed at each time point. Energy and nutrient intake were assessed using 4-day food records, and physical activity was evaluated via questionnaires and accelerometry. Total energy expenditure (TEE) was calculated using a formula based on lean mass (LM) and fat mass (FM) from DXA. Statistical analyses included descriptive statistics, linear regression (to assess associations between TEI and adiposity measures and TEE), and power models (to analyze the relationship between proportional energy intake from macronutrients and TEI). Mixture modeling was employed to disentangle the interactions between macronutrients on TEI using the nutritional geometry framework. Subgroup analyses explored the influence of sex, pubertal stage, and study group on the observed relationships.

The study included 422 children at TO, 387 at T1, and 229 at T2. Proportional energy intake from proteins was inversely associated with TEI at all three ages, following power functions (mean leverage strength L = -0.36, -0.26, -0.25 at TO, T1, and T2 respectively; all p<0.001). Mixture modeling indicated that variation in TEI was primarily associated with the proportional intake of energy from proteins, not fats or carbohydrates. At all ages, TEI was not significantly associated with BMI z-score or waist circumference but was positively associated with TEE (all p<0.001). Subgroup analyses revealed that male sex was associated with higher TEI compared to females at all ages. Pubertal status and study group did not significantly affect the relationship between protein intake and TEI.

This study provides the first evidence of PL in a general population sample of children and adolescents. The lack of association between TEI and adiposity measures is likely due to the counterbalancing effect of increased TEE, suggesting the cohort maintained energy balance. The relatively low prevalence of overweight and obesity in the cohort and its generally healthy diet might also contribute to this finding. Underreporting of TEI in dietary assessments, a known phenomenon in adolescents and obese individuals, could also play a role. However, if TEI was consistently higher than reported, a higher prevalence of overweight and obesity would be expected. The observed PL effect is expected to be more pronounced in populations consuming diets rich in ultra-processed foods, which are typically low in protein and high in energy-dense carbohydrates and fats. Future research should focus on cohorts with varying dietary habits to assess the generalizability of these findings.

This study provides novel evidence for PL in a representative cohort of children and adolescents. While PL was observed, it did not translate to increased adiposity in this cohort, possibly due to compensatory increases in TEE, a generally healthy diet, and low obesity prevalence. Future studies should investigate the interplay between PL, dietary patterns, and adiposity in diverse populations, particularly those consuming diets high in ultra-processed foods.

The cross-sectional design limits the ability to establish causal relationships between macronutrient intake and changes in TEI. The study population exhibited a relatively low prevalence of overweight and obesity and consumed a generally healthy diet, which may limit the generalizability of the findings to populations with different dietary habits and higher obesity prevalence. The subgroup analyses on the association between PL and puberty were based on a smaller number of participants and require further investigation.