AI Diet Plans: Risks to Teen Health Revealed in New Study

ISTANBUL / LONDON – A new study reveals potential risks associated with AI-powered diet plans for adolescents. These plans, often generated by popular chatbots, may underestimate caloric needs and provide an imbalanced distribution of nutrients, raising concerns among health experts.

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As more young people turn to artificial intelligence for personalized weight management guidance, researchers are examining the safety and accuracy of these AI-generated diets. A recently published study in Frontiers in Nutrition found that computer-generated meal plans often fall short of meeting basic caloric requirements and lack a proper balance of essential nutrients. This could potentially expose adolescents to nutritional deficiencies during a critical period of growth and development.

Rising rates of childhood and adolescent obesity worldwide are a significant public health concern, carrying both short- and long-term health risks including an increased risk of type 2 diabetes, high blood pressure, and sleep apnea. Health professionals generally recommend that young people manage their weight through a combination of increased physical activity, behavioral changes, and specialized dietary guidance.

With access to professional nutritional counseling often limited by cost and availability, many adolescents are seeking health information online. AI tools that generate human-like text in response to user queries have become particularly popular resources for dietary advice. Previous research has explored how well these text-generating programs can address general nutrition questions or plan meals for adults.

Still, few studies have investigated the safety of these tools when creating diets specifically for teenagers. Adolescence is a time of intense physical and cognitive maturation, meaning young people have specific nutritional needs that differ from those of adults. Ayşe Betül Bilen, assistant professor of nutrition and dietetics at Istanbul Atlas University in Turkey, led a research team to address this question.

Bilen and her colleagues wanted to determine whether popular chatbots could create safe and balanced meal plans for young people without professional oversight. The research team observed that adolescents often enter simple queries into search engines, rather than providing detailed medical information. To simulate how the algorithms would respond to a typical teenager, the researchers decided to compare the software’s output to a professional standard.

The researchers tested five widely used AI models: OpenAI’s ChatGPT, Google’s Gemini, Microsoft’s Bing Chat, Anthropic’s Claude, and Perplexity. The team used the free versions of these tools, as a typical teenager would most likely utilize the options without a paywall.

To mimic the diverse needs of real adolescents, the team created four hypothetical profiles of 15-year-olds. These profiles represented a boy and a girl classified as overweight, as well as a boy and a girl classified as obese. The researchers determined these categories based on body mass index percentiles, a standard measure that compares a child’s weight and height to growth charts for their specific age and gender.

For the purposes of this study, the 85th to 94th percentile was defined as overweight, and the 95th percentile and above as obese. For each profile, the researchers asked the five chatbots to create a three-day meal plan for weight reduction. The instructions requested three main meals and two snacks per day, with portion sizes specified in grams or milliliters.

The prompts specifically requested foods readily available in Turkey, where the study was conducted. The researchers did not provide target calorie numbers or specific dietary guidelines in their inputs, aiming to replicate the natural language a teenager might use when asking a computer for help.

Each software program was run in two separate sessions for the four profiles, resulting in a total of 60 days of computer-generated meals. The researchers then needed a benchmark to evaluate these digital menus. A pediatric dietitian created a one-day reference plan for each of the four adolescent profiles.

These human-created plans strictly followed international guidelines for energy balance and nutrient distribution. The research team used a specialized nutrition database to analyze the content of both the computer-generated and human-created meal plans, looking at the total calories provided as well as the balance of macronutrients.

Macronutrients are the main building blocks of our diet, categorized as carbohydrates, proteins, and fats. The analysis revealed a substantial calorie deficit in the computer-generated diets. On average, the algorithms underestimated the adolescents’ daily energy needs by nearly 700 calories compared to the dietitian’s plan.

A deficit of this magnitude is equivalent to skipping an entire meal, which the researchers considered potentially harmful to metabolic health and eating behaviors over time. “We show that diet plans generated by AI models tend to significantly underestimate total energy and key nutrient intake compared to guideline-based plans created by a registered dietitian,” Bilen said in a press release.

The computer programs also struggled to provide the correct balance of macronutrients. According to established health guidelines, adolescents should obtain approximately 45 to 50 percent of their daily calories from carbohydrates. In the meal plans generated by the algorithms, carbohydrates accounted for only 32 to 36 percent of total energy.

This sharp reduction in carbohydrates often leads to a decrease in fiber, which is essential for healthy digestion and maintaining a balanced gut microbiome. To compensate for the lack of carbohydrates, the AI models relied heavily on proteins and fats. The digital plans recommended that proteins provide up to 24 percent of daily energy, exceeding the standard recommendation of 15 to 20 percent.

A diet overly rich in protein can force the kidneys to work harder than normal and increase the amount of calcium lost through urine. Fats made up about 41 to 45 percent of the computer-generated calories, well above the ideal target of 30 to 35 percent. “AI-generated diet plans consistently deviated from the recommended macronutrient balance, which is particularly problematic for adolescents,” Bilen emphasized.

Bilen suggested that the software may be drawing information from trendy internet diets. Many popular weight loss programs favor protein-rich, carbohydrate-restricted meals. As AI programs learn by scanning large volumes of online text, they often replicate these popular concepts rather than prioritizing age-appropriate medical guidelines.

“AI models are primarily trained to generate responses that appear plausible and user-friendly, rather than being clinically precise,” Bilen said. “Our findings suggest they may rely on generalized or popular diet patterns rather than fully integrating age-specific nutritional requirements.”

The researchers also reviewed the computer menus for micronutrients—vitamins and minerals the body needs in small amounts to function properly. The algorithms showed high inconsistency in this area. Some programs delivered far too much vitamin D and folate, while others overestimated calcium and phosphorus.

Trace elements like iron, zinc, copper, and manganese also varied widely depending on which program the researchers tested. No single computer model consistently matched the human dietitian across all nutrition categories. The research team noted that adolescents are already at risk for vitamin and mineral deficiencies, and relying on an algorithm could exacerbate these problems.

The researchers acknowledged some limitations of their work. Because the study was based on hypothetical profiles, it did not follow real adolescents consuming the computer-generated meals. This means the researchers were unable to observe actual metabolic changes or shifts in eating behavior in human subjects.

The study did not account for participants’ prior dietary habits, as this would have required making assumptions about their daily routines. The prompts were also written in Turkish, which could limit the applicability of the findings to other languages or cultural contexts. AI software is rapidly updated, so the specific errors found in these versions may change as the programs are refined over time.

The researchers suggested that future studies should track real dietary habits alongside more advanced versions of the software. Health experts advise that algorithm-based tools should not replace traditional nutritional counseling. While technology could serve as a basic educational tool, it currently lacks the precision to safely manage the health of adolescents.

Adolescents and their parents should consult qualified medical professionals before starting restrictive weight loss programs. “Adolescence is a critical phase for physical growth, bone development, and cognitive maturation,” Bilen concluded. “Lower energy and carbohydrate intake, combined with increased protein and fat proportions, can pose risks during the growth phase of adolescents.”

The study, “Artificial intelligence diet plans underestimate nutrient intake compared to dietitians in adolescents,” was authored by Ayşe Betül Bilen, Gülen Ecem Kalkan, and Hülya Yılmaz Önal.

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