It’s perfectly fine if you choose a toasted bagel for breakfast while your partner opts for eggs. In fact, this difference might actually assist you in shedding some pounds.
It’s perfectly okay to select a toasted bagel for breakfast when your partner goes for eggs. According to recent research from the University of Waterloo, this variance might be beneficial for your weight loss efforts.
This study used a mathematical model to analyze the metabolisms of men and women. It found that men’s metabolisms tend to react more positively to high-carbohydrate meals, such as those rich in oats and grains, after several hours of fasting. On the other hand, women typically do better with meals that are higher in fat, like omelettes and avocados.
“Lifestyle plays a significant role in our overall health,” explained Stéphanie Abo, the lead author of the study and a PhD candidate in Applied Mathematics. “In our busy lives, it’s crucial to recognize how seemingly minor choices, like what we have for breakfast, can influence our health and energy levels. Whether you’re looking to lose weight, maintain your current weight, or simply boost your energy, understanding how your diet affects your metabolism is essential.”
This research addresses a gap in knowledge regarding the differences between how men and women metabolize fat. “There is often less research conducted on women’s bodies compared to men’s,” noted Anita Layton, a professor of Applied Mathematics and the Canada 150 Research Chair in Mathematical Biology and Medicine.
“By developing mathematical models based on existing data, we can quickly assess various hypotheses and adjust experiments in ways that would be difficult to execute with human participants,” Layton said.
“Despite the common belief that women, who typically have a higher body fat percentage, should burn less fat for energy, that’s not the case,” Layton continued. “Our model’s findings indicate that while women store more fat right after meals, they also burn a greater amount of fat during fasting periods.”
In the future, the researchers aim to create more advanced metabolism models that consider various factors beyond biological sex, such as individual weight, age, or menstrual cycle phase.
