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Unhealthy dietary habits and sedentarism coexist with a rising incidence of excess weight and associated comorbidities. We aimed to analyze the dietary and drinking patterns of patients with excess weight, their main characteristics, plausible gender differences and impact on cardiometabolic risk factors, with a particular focus on the potential contribution of beer consumption. Data from 200 consecutive volunteers (38 ± 12 years; 72% females) living with overweight or class I obesity attending the obesity unit to lose weight were studied. Food frequency questionnaires and 24 h recalls were used. Reduced-rank regression (RRR) analysis was applied to identify dietary patterns (DPs). Anthropometry, total and visceral fat, indirect calorimetry, physical activity level, comorbidities and circulating cardiometabolic risk factors were assessed. Study participants showed high waist circumference, adiposity, insulin resistance, dyslipidemia, pro-inflammatory adipokines and low anti-inflammatory factors like adiponectin and interleukin-4. A low-fiber, high-fat, energy-dense DP was observed. BMI showed a statistically significant (p < 0.05) correlation with energy density (r = 0.80) as well as percentage of energy derived from fat (r = 0.61). Excess weight was associated with a DP low in vegetables, legumes and whole grains at the same time as being high in sweets, sugar-sweetened beverages, fat spreads, and processed meats. RRR analysis identified a DP characterized by high energy density and saturated fat exhibiting negative loadings (>−0.30) for green leafy vegetables, legumes, and fruits at the same time as showing positive factor loadings (>0.30) for processed foods, fat spreads, sugar-sweetened beverages, and sweets. Interestingly, for both women and men, wine represented globally the main source of total alcohol intake (p < 0.05) as compared to beer and distillates. Beer consumption cannot be blamed as the main culprit of excess weight. Capturing the DP provides more clinically relevant and useful information. The focus on consumption of single nutrients does not resemble real-world intake behaviors.

Adolphe Quételet, a 19th-century Belgian sociologist and statistician, pioneered the incorporation of statistics into social sciences. He initiated the development of anthropometry since he was interested in identifying the proportions of the 'ideal man'. He devised a ratio between weight and height, originally termed the Quételet Index, and today widely known and used as the body mass index or BMI. In 1835, he demonstrated that a normal curve accommodates the distribution of human traits articulating his reasoning on human variance around the average. Quételet's long-lasting legacy of the establishment of a simple measure to classify people's weight relative to an ideal for their height endures today with minor variations having dramatically influenced public health agendas. While being very useful, the limitations of the BMI are well known. Thus, revisiting the beyond BMI paradigm is a necessity in the era of precision medicine with morphofunctional assessment representing the way forward via incorporation of body composition and functionality appraisal. While healthcare systems were originally designed to address acute illnesses, today's demands require a radical rethinking together with an original reappraisal of our diagnosis and treatment approaches from a multidimensional perspective. Embracing new methodologies is the way forward to advance the field, gain a closer look at the underlying pathophysiology of excess weight, keep the spotlight on improving diagnostic performance and demonstrate its clinical validity. In order to provide every patient with the most accurate diagnosis together with the most appropriate management, a high degree of standardization and personalization is needed., (© 2024 The Authors. European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation.)

Unhealthy dietary habits and sedentarism coexist with a rising incidence of excess weight and associated comorbidities. We aimed to analyze the dietary and drinking patterns of patients with excess weight, their main characteristics, plausible gender differences and impact on cardiometabolic risk factors, with a particular focus on the potential contribution of beer consumption. Data from 200 consecutive volunteers (38 ± 12 years; 72% females) living with overweight or class I obesity attending the obesity unit to lose weight were studied. Food frequency questionnaires and 24 h recalls were used. Reduced-rank regression (RRR) analysis was applied to identify dietary patterns (DPs). Anthropometry, total and visceral fat, indirect calorimetry, physical activity level, comorbidities and circulating cardiometabolic risk factors were assessed. Study participants showed high waist circumference, adiposity, insulin resistance, dyslipidemia, pro-inflammatory adipokines and low anti-inflammatory factors like adiponectin and interleukin-4. A low-fiber, high-fat, energy-dense DP was observed. BMI showed a statistically significant ( p < 0.05) correlation with energy density (r = 0.80) as well as percentage of energy derived from fat (r = 0.61). Excess weight was associated with a DP low in vegetables, legumes and whole grains at the same time as being high in sweets, sugar-sweetened beverages, fat spreads, and processed meats. RRR analysis identified a DP characterized by high energy density and saturated fat exhibiting negative loadings (>-0.30) for green leafy vegetables, legumes, and fruits at the same time as showing positive factor loadings (>0.30) for processed foods, fat spreads, sugar-sweetened beverages, and sweets. Interestingly, for both women and men, wine represented globally the main source of total alcohol intake ( p < 0.05) as compared to beer and distillates. Beer consumption cannot be blamed as the main culprit of excess weight. Capturing the DP provides more clinically relevant and useful information. The focus on consumption of single nutrients does not resemble real-world intake behaviors.

Academic medicine fosters research that moves from discovery to translation, at the same time as promoting education of the next generation of professionals. In the field of obesity, the supposed integration of knowledge, discovery and translation research to clinical care is being particularly hampered. The classification of obesity based on the body mass index does not account for several subtypes of obesity. The lack of a universally shared definition of "obesities" makes it impossible to establish the real burden of the different obesity phenotypes. The individual's genotype, adipotype, enterotype and microbiota interplays with macronutrient intake, appetite, metabolism and thermogenesis. Further investigations based on the concept of differently diagnosed "obesities" are required., (© 2022 The Authors. European Journal of Clinical Investigation published by John Wiley & Sons Ltd on behalf of Stichting European Society for Clinical Investigation Journal Foundation.)