Caution, "normal" BMI: health risks associated with potentially masked individual underweight-EPMA Position Paper 2021

Abstract

An increasing interest in a healthy lifestyle raises questions about optimal body weight. Evidently, it should be clearly discriminated between the standardised "normal" body weight and individually optimal weight. To this end, the basic principle of personalised medicine "one size does not fit all" has to be applied. Contextually, "normal" but e.g. borderline body mass index might be optimal for one person but apparently suboptimal for another one strongly depending on the individual genetic predisposition, geographic origin, cultural and nutritional habits and relevant lifestyle parameters-all included into comprehensive individual patient profile. Even if only slightly deviant, both overweight and underweight are acknowledged risk factors for a shifted metabolism which, if being not optimised, may strongly contribute to the development and progression of severe pathologies. Development of innovative screening programmes is essential to promote population health by application of health risks assessment, individualised patient profiling and multi-parametric analysis, further used for cost-effective targeted prevention and treatments tailored to the person. The following healthcare areas are considered to be potentially strongly benefiting from the above proposed measures: suboptimal health conditions, sports medicine, stress overload and associated complications, planned pregnancies, periodontal health and dentistry, sleep medicine, eye health and disorders, inflammatory disorders, healing and pain management, metabolic disorders, cardiovascular disease, cancers, psychiatric and neurologic disorders, stroke of known and unknown aetiology, improved individual and population outcomes under pandemic conditions such as COVID-19. In a long-term way, a significantly improved healthcare economy is one of benefits of the proposed paradigm shift from reactive to Predictive, Preventive and Personalised Medicine (PPPM/3PM). A tight collaboration between all stakeholders including scientific community, healthcare givers, patient organisations, policy-makers and educators is essential for the smooth implementation of 3PM concepts in daily practice.

Keywords: Adults; Anorexia athletica; Anthropometrics; Artificial intelligence in medicine; BMI deviation; Big data management; Biomarker panel; Body fluids; Body weight; COVID-19; Cancers; Cardiovascular disease; Communicable; Deficits; Disease development; Elderly; Endothelin-1; Fat; Flammer syndrome; Health economy; Health policy; Healthcare; Hypoxic effects; Immune system; Individualised patient profile; Inflammation; Innovative population Screening Programme; Intentional; Manifestation; Medical imaging; Metabolic pathways; Microbiome; Modelling; Molecular patterns; Multi-level diagnostics; Multi-parametric analysis; Neurodegeneration; Neurology; Non-communicable disorders; Nutrition; Overweight; Pathology; Population health; Predictive preventive personalised medicine (3PM/PPPM); Pregnancy; Progression; ROS; Reproductive dysfunction; Sports medicine; Stroke; Systemic ischemia; Underweight; Unintentional; Vasoconstriction; Weight loss; Well-being; Wound healing; Youth.

Fig. 1

Anorexic versus obese phenotype: The paradox of the similarity of health risks; the figure is adapted from [4]

Fig. 2

A population-based cohort study by Bhaskaran et al. demonstrated the association between BMI and cause-specific mortality, exemplified here for never-smokers diagnosed with A prostate cancer versus B uterus cancer; the horizontal axis indicates BMI (kg/m²) and the vertical axis indicates hazard ratio (95% confidence interval); the image is adapted from [5]

Fig. 3

Health risks potentially associated with low body weight; Explanatory notes: BMI classification: underweight—BMI < 18.5 kg/m²; normal weight—BMI = 18.5 to 25 kg/m²; overweight—BMI ≥ 25 to < 30 kg/m²; obese—BMI ≥ 30 to < 35 kg/m²; and severely obese—BMI ≥ 35 kg/m² [40, 41]. Selected suggested mechanisms behind increased risk of specific health complication associated with underweight include the following: abnormal nutritional status, low body fat (e.g. anorexia athletica) or low muscle mass, muscular atrophy [42], cardiovascular abnormalities, valvular dysfunction, compromised immunity [43]; cancer—particularly poor outcomes of some cancers, potentially decreased tolerability/effectiveness of cancer treatment e.g. due to lower haemoglobin and albumin resulting from abnormal nutritional status, cachexia, impaired anti-tumour immunity [44], loss of muscle fat mass, sarcopenia [45], increased risk of several cancer types and metastatic disease [6, 46, 47]; impaired healing and increased post-surgical complications—abnormal nutritional status, insufficient energy supply, shifted metabolic pathways and microbiome alterations [4, 24, 48],  potentially low preoperative haemoglobin [49, 50]; reproductive dysfunction—disruption of hypothalamic-pituitary–gonadal axis leading to hypothalamic anovulation [51], ovulatory dysfunction [52], negative effects on IVF parameters [–55]; compromised immunity—abnormal nutritional status, lymphopenia [56]; respiratory infections including COVID-19—malnutrition [57], coexisting chronic conditions [58], immuno-suppression as a result of malnutrition [59]; eating disorders (anorexia nervosa)—negative effects on overall and reproductive health [60]; neurological disorders such as young stroke [12] and abnormal pain sensitivity / perception [4, 7]; abnormal sleep patterns [7, 11, 15] and depression [61]; primary vascular dysregulation—abnormal nutrition, low energy supply, Flammer syndrome, high Endothelin-1 level in blood plasma, increased stress sensitivity, amongst others [4, 9, 15, 17, 62]; Sicca syndrome with severe complications [11, 13, 15].

Fig. 4

Ultrasound imaging as the diagnostic tool to discriminates between A abnormally low and B excessive versus C normal abdominal and visceral fat distribution and D SAT patterns in visceral fat redistribution; evident gender difference is well respected by gender-specific patterns of fat distribution, namely for males (B and D) and females (A and C). Notably, specific movement patterns at breathing further contribute to the correctness of the fat tissue measurement in abdominal cavity. The scanning was performed in the sagittal plane along the linea alba; the figure is adapted from [4]