Body composition, lung function, blood pressure, and muscular strength: a comparative study
Background: The loss of balance between components of body composition is significantly linked to a wide range of adverse clinical outcomes. Whilst the sharp rise in the rate of adiposity-based chronic diseases has caused substantial health concerns across the globe, sarcopenia has emerged as an important risk factor for increased morbidity and mortality among the aging population. Therefore, assessment of body composition phenotypes using the conceptual model of metabolic capacity and metabolic load enables an insightful evaluation of metabolic homeostasis association with health outcomes. Nevertheless, the evidence on such associations in the adult population is still lacking. Objectives: To examine the relationship of anthropometric measures with total and segmental adiposity and muscularity; to investigate variations of blood pressure across body composition phenotypes; to explore the interaction effect of fatness and leanness on lung function, and to evaluate bidirectional association of lung function and blood pressure. Study design and subjects: This project was a cross-sectional study of fifty healthy adults (22 men, 28 women) aged 19-65 years old. Anthropometric, body composition (Tanita MC980 and InBody 720 segmental multifrequency bioelectric impedance analysers, and the BODPOD air displacement plethysmography system), blood pressure (OMRON M7 automated oscillometric monitor), grip strength (Takei 5001 analogue dynamometer) and spirometric (COSMED Quark PFT) measurements were carried out in Nutrition Physiology Laboratory at London Metropolitan University from 2016 to 2018. Statistical analysis: Moderation analyses of the associations between body composition, blood pressure and lung function were conducted by the PROCESS modelling tool for SPSS. Results: None of the anthropometric measures were exclusively related to muscle mass. Neck circumference (NC) and upper arm circumference (AC) were the strongest and a body shape index (ABSI) was the only negative predictor of total and segmental muscularity in the entire population. Also, waist to height ratio (WHtR), waist circumference (WC), waist to hip ratio (WHR) and body mass index (BMI) were all strong correlates of total, truncal, visceral and upper arm fatness. None of the anthropometric measurements showed moderate or strong correlations with lower limb fatness. Fat mass (FM) to fat-free mass (FFM) ratio was only significantly associated with diastolic pressure (DBP) (ꞵ=17.6, p<0.001) whereas truncal FM (TFM) to appendicular skeletal muscle mass (ASM) ratio was associated significantly with systolic pressure (SBP) (ꞵ=15.94, p<0.01), DBP (ꞵ=27.47, p<0.001) and pulse pressure (ꞵ=-11.38, p<0.01). Stature-normalised truncal and appendicular adiposity (TFMI, AFMI) impaired lung function (FEV1, FVC and FEF25-75%) respectively at high levels of truncal and appendicular muscularity (TSMI, ASMI). The negative impact of whole-body (high FM/FFM) and segmental (high TFM/ASM) metabolic overload on expiratory flow rate (FEV1) was respectively conditioned on low DBP and high SBP (ꞵ=- .104, p<0.01, ꞵ=-.163; p<0.001). Negative effect of increased FM/FFM and TFM/ASM on FEV1 and FVC was also operable at high levels of grip strength. There was a bidirectional association between lung function and systemic blood pressure. SBP and DBP were independently and negatively associated with FEV1 (ꞵ=-.011 and -.019; p<0.001) and FVC (ꞵ=-.011 and -.022; p<0.001). FEV1 and FVC demonstrated inverse associations with SBP (standardised ꞵ=-.38 and -.30; p<0.001) and DBP (standardised ꞵ=-.35 and -.40; p<0.001). Notably, the effect of FEV1 and FVC on SBP was operated at higher levels of visceral adiposity whilst their influence on DBP was conditioned on higher levels of FFMI. Conclusion: Whole-body and segmental metabolic homeostasis, pulmonary function and systemic blood pressure are complexly cross-linked. Therefore, phenotyping the individuals with or at risk of respiratory diseases and/or cardiometabolic disorders by their total and regional body composition, spirometric, and haemodynamic characteristics may result in more accurate risk stratification, personalised care and effective management strategies, leading to improved clinical outcomes, survival and quality of life.
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