The present systematic review and meta-analysis sought to evaluate the effects of conjugated linoleic acid (CLA) supplementation on cardiovascular risk factors in patients at risk of CVD. Relevant studies were obtained by searching the PubMed, SCOPUS and Web of Science databases (from inception to January 2023). Weighted mean differences (WMD) and 95% CI were pooled using a random-effects model. Heterogeneity, sensitivity analysis and publication bias were reported using standard methods. A pooled analysis of 14 randomised controlled trials (RCT) with 17 effect sizes revealed that CLA supplementation led to significant reductions in body weight (WMD: −0·72 kg, 95% CI: −1·11, −0·33, P < 0·001), BMI (WMD: −0·22 kg/m2, 95% CI: −0·44, −0·00, P = 0·037) and body fat percentage (BFP) (WMD: −1·32 %, 95% CI: −2·24, −0·40, P = 0·005). However, there was no effect on lipid profile and blood pressure in comparison with the control group. In conclusion, CLA supplementation may yield a small but significant beneficial effect on anthropometric indices in patients at risk of CVD. Moreover, CLA seems not to have adverse effects on lipid profiles and blood pressure in patients at risk of CVD. It should be noted that the favourable effects of CLA supplementation on anthropometric variables were small and may not reach clinical importance.

Skeletal muscle is integral to the metabolism and utilisation of macronutrients; however, substantial muscle loss and morphological changes occur with ageing. These are associated with loss of muscle function and accelerate rapidly from the age of 60 years, leading to the conditions of sarcopenia and frailty. As the relationship between muscle ageing and macronutrient metabolism and utilisation has seen limited research to date, this review focuses on the interactions between skeletal muscle changes during ageing, metabolism and utilisation of fat, carbohydrates and overall energy expenditure.

Skeletal muscle contributes less to resting energy expenditure during ageing, potentially contributing to onset of obesity from middle age. Age-related changes to skeletal muscle lead to glucose dysregulation, with consequent reduction in glycaemic control, increased insulin resistance and ultimately onset of type-2 diabetes. Recent studies indicate that high total fat and SFA intake are detrimental to skeletal muscle, while higher intakes of PUFA are protective. Age-associated changes in skeletal muscle may also reduce total fatty acid utilisation.

In conclusion, further research is needed to understand the relationships between macronutrient metabolism and utilisation and age-related changes to skeletal muscle. No dietary recommendations exist specifically for skeletal muscle health during ageing, but we advise individuals to follow healthy eating guidelines, by consuming sufficient protein, fruit and vegetables, and limited SFA and to maintain physically active lifestyles. Clinicians responsible for managing type-2 diabetes need to be aware of growing evidence relating age-related skeletal muscle changes to diabetes onset and progression.

An awareness of the importance of nutritional status in hospital settings began more than 40 years ago. Much has been learned since and has altered care. For the past 40 years several large studies have shown that cancer patients are amongst the most malnourished of all patient groups. Recently, the use of gold-standard methods of body composition assessment, including computed tomography, has facilitated the understanding of the true prevalence of cancer cachexia (CC). CC remains a devastating syndrome affecting 50–80 % of cancer patients and it is responsible for the death of at least 20 %. The aetiology is multifactorial and complex; driven by pro-inflammatory cytokines and specific tumour-derived factors, which initiate an energy-intensive acute phase protein response and drive the loss of skeletal muscle even in the presence of adequate food intake and insulin. The most clinically relevant phenotypic feature of CC is muscle loss (sarcopenia), as this relates to asthenia, fatigue, impaired physical function, reduced tolerance to treatments, impaired quality of life and reduced survival. Sarcopenia is present in 20–70 % depending on the tumour type. There is mounting evidence that sarcopenia increases the risk of toxicity to many chemotherapy drugs. However, identification of patients with muscle loss has become increasingly difficult as 40–60 % of cancer patients are overweight or obese, even in the setting of metastatic disease. Further challenges exist in trying to reverse CC and sarcopenia. Future clinical trials investigating dose reductions in sarcopenic patients and dose-escalating studies based on pre-treatment body composition assessment have the potential to alter cancer treatment paradigms.

The aim of this review is to extend present concepts of body composition and to integrate it into physiology. In vivo body composition analysis (BCA) has a sound theoretical and methodological basis. Present methods used for BCA are reliable and valid. Individual data on body components, organs and tissues are included into different models, e.g. a 2-, 3-, 4- or multi-component model. Today the so-called 4-compartment model as well as whole body MRI (or computed tomography) scans are considered as gold standards of BCA. In practice the use of the appropriate method depends on the question of interest and the accuracy needed to address it. Body composition data are descriptive and used for normative analyses (e.g. generating normal values, centiles and cut offs). Advanced models of BCA go beyond description and normative approaches. The concept of functional body composition (FBC) takes into account the relationships between individual body components, organs and tissues and related metabolic and physical functions. FBC can be further extended to the model of healthy body composition (HBC) based on horizontal (i.e. structural) and vertical (e.g. metabolism and its neuroendocrine control) relationships between individual components as well as between component and body functions using mathematical modelling with a hierarchical multi-level multi-scale approach at the software level. HBC integrates into whole body systems of cardiovascular, respiratory, hepatic and renal functions. To conclude BCA is a prerequisite for detailed phenotyping of individuals providing a sound basis for in depth biomedical research and clinical decision making.