Distinct phenotypic characteristics of normal-weight adults at risk of developing cardiovascular and metabolic diseases

Weight/height2: Mathematical overview of the world's most widely used adiposity index

A footnote in Adolphe Quetelet's classic 1835 Treatise on Man described his algebraic analysis of how body weight ( W ) varies with height ( H ) in adult males and females. Using data on 12 short and 12 tall subjects of each sex, Quetelet established the rule that W is approximately proportional ( ∝ ) to H2 in adults; that is, W ∝ H 2 when W ≈ α H 2 for some constant α . Quetelet's Rule ( W ∝ H 2 ), transformed and renamed in the twentieth century to body mass index ( BMI = W / H 2 ), is now a globally applied phenotypic descriptor of adiposity at the individual and population level. The journey from footnote to ubiquitous adiposity measure traveled through hundreds of scientific reports and many more lay publications. The recent introduction of highly effective pharmacologic weight loss treatments has heightened scrutiny of BMI's origins and appropriateness as a gateway marker for diagnosing and monitoring people with obesity. This contemporary context prompted the current report that delves into the biological and mathematical paradigms that underlie the simple index BMI = W / H 2 . Students and practitioners can improve or gain new insights into their understanding of BMI's historical origins and quantitative underpinning from the provided overview, facilitating informed use of BMI and related indices in research and clinical settings.

Skeletal muscle estimation: A review of techniques and their applications

Quantifying skeletal muscle size is necessary to identify those at risk for conditions that increase frailty, morbidity, and mortality, as well as decrease quality of life. Although muscle strength, muscle quality, and physical performance have been suggested as important assessments in the screening, prevention, and management of sarcopenic and cachexic individuals, skeletal muscle size is still a critical objective marker. Several techniques exist for estimating skeletal muscle size; however, each technique presents with unique characteristics regarding simplicity/complexity, cost, radiation dose, accessibility, and portability that are important factors for assessors to consider before applying these modalities in practice. This narrative review presents a discussion centred on the theory and applications of current non-invasive techniques for estimating skeletal muscle size in diverse populations. Common instruments for skeletal muscle assessment include imaging techniques such as computed tomography, magnetic resonance imaging, peripheral quantitative computed tomography, dual-energy X-ray absorptiometry, and Brightness-mode ultrasound, and non-imaging techniques like bioelectrical impedance analysis and anthropometry. Skeletal muscle size can be acquired from these methods using whole-body and/or regional assessments, as well as prediction equations. Notable concerns when conducting assessments include the absence of standardised image acquisition/processing protocols and the variation in cut-off thresholds used to define low skeletal muscle size by clinicians and researchers, which could affect the accuracy and prevalence of diagnoses. Given the importance of evaluating skeletal muscle size, it is imperative practitioners are informed of each technique and their respective strengths and weaknesses.

Association between modifiable lifestyle pattern and periodontitis: a cross-sectional study based on NHANES

BACKGROUND

Periodontitis can be avoided with a healthy lifestyle. However, studies have only looked at one lifestyle, ignoring the connection between lifestyle patterns and periodontitis. The purpose of this study was to look at the association between modifiable lifestyle patterns and periodontitis.

METHODS

Data were obtained from the National Health and Nutrition Examination Survey in 2009-2010 and 2011-2012. Smoke, drink, exercise, sleep duration, oral exams, and self-rated oral health were all lifestyle factors. The CDC/AAP classification/case definition was used to evaluate periodontitis. Drawing upon latent class analysis, distinct patterns of lifestyle were identified, with each participant exclusively affiliated with a single pattern. The association between lifestyle classes and periodontitis was then examined using ordinal logistic regression.

RESULTS

4686 (52%) of the total 9034 participants, with a mean age of 54.08, were women. Three lifestyle latent classes were found by fitting 2-10 models: "Class 1" (52%), " Class 2" (13%), and " Class 3" (35%). The "Class 1" displayed a prevalence of oral examination (75%), favorable self-rated oral health (92%), and engagement in physical activity (50%). The 'Class 2' exhibited the lowest alcohol consumption (64%) and smoking rates (73%) but the highest prevalence of physical inactivity (98%). The 'Class 3' showed a tendency for smoking (72%), alcohol consumption (78%), shorter sleep duration (50%), absence of oral examinations (75%), and suboptimal self-rated oral health (68%). The influencing variables for the latent classes of lifestyle were age, education, and poverty level. Periodontitis risk may rise by 24% for each additional unhealthy lifestyle practiced by participants (OR = 1.24, 95% CI: 1.18-1.31). The 'Class 3' (OR = 1.80, 95% CI: 1.52-2.13) had a greater risk of periodontitis compared to the 'Class 1'.

CONCLUSIONS

Our analysis revealed that unhealthy lifestyle patterns are associated with periodontitis. These different lifestyle patterns need to be taken into account when developing public health interventions and clinical care.

miR-21, miR-221, miR-29 and miR-34 are distinguishable molecular features of a metabolically unhealthy phenotype in young adults

Discrepancies between the measurement of body mass index (BMI) and metabolic health status have been described for the onset of metabolic diseases. Studying novel biomarkers, some of which are associated with metabolic syndrome, can help us to understand the differences between metabolic health (MetH) and BMI. A group of 1469 young adults with pre-specified anthropometric and blood biochemical parameters were selected. Of these, 80 subjects were included in the downstream analysis that considered their BMI and MetH parameters for selection as follows: norm weight metabolically healthy (MHNW) or metabolically unhealthy (MUNW); overweight/obese metabolically healthy (MHOW) or metabolically unhealthy (MUOW). Our results showed for the first time the differences when the MetH status and the BMI are considered as global MetH statures. First, all the evaluated miRNAs presented a higher expression in the metabolically unhealthy group than the metabolically healthy group. The higher levels of leptin, IL-1b, IL-8, IL-17A, miR-221, miR-21, and miR-29 are directly associated with metabolic unhealthy and OW/OB phenotypes (MUOW group). In contrast, high levels of miR34 were detected only in the MUNW group. We found differences in the SIRT1-PGC1α pathway with increased levels of SIRT1+ cells and diminished mRNA levels of PGCa in the metabolically unhealthy compared to metabolically healthy subjects. Our results demonstrate that even when metabolic diseases are not apparent in young adult populations, MetH and BMI have a distinguishable phenotype print that signals the potential to develop major metabolic diseases.

Characteristics of Normal Weight Insulin-Resistant Adults with Unfavorable Health Outcomes

Background: Insulin resistance can be present in otherwise healthy, normal weight adults. Whether there are phenotype/sex-differences between normal weight insulin-resistant (NWIR) and normal weight insulin-sensitive (NWIS) Caucasians and whether there are differences in adverse health outcomes are unknown. Our goal was to define phenotypes and intermediate-term health outcomes of NWIR versus NWIS Caucasian adults. Methods: We analyzed data from 227 healthy volunteers body mass index 18 to <25.0 kg/m2 who underwent insulin clamp studies between January 1987 and January 2017 at Mayo Clinic to identify those in the top (NWIS, n = 56) and bottom (NWIR, n = 56) quartiles of insulin action. We compared the phenotypical characteristics and were able to collect medical records data for 80% of NWIS and 88% of NWIR to identify time to onset of hypertension, hyperglycemia, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and all cause death; the follow-up averaged 11 (4, 20) years. Results: Body fat was significantly greater and peak VO2 was significantly less in both NWIS than NWIR males and females. Only in females was abdominal subcutaneous fat by computed tomography significantly greater in NWIR than NWIS. In NWIR males high-density lipoprotein-cholesterol and fat free mass were significantly less, and fasting insulin was greater than NWIS males. For the entire NWIS population, Kaplan-Meier disease-free survival analysis showed longer times free of hypertension, hyperglycemia, and some cardiovascular diseases than for NWIR. Conclusions: There are sex-specific phenotypes of NWIR in Caucasian adults. NWIR may be associated with accelerated onset of some adverse medical outcomes.

Total and regional appendicular skeletal muscle mass prediction from dual-energy X-ray absorptiometry body composition models

Sarcopenia, sarcopenic obesity, frailty, and cachexia have in common skeletal muscle (SM) as a main component of their pathophysiology. The reference method for SM mass measurement is whole-body magnetic resonance imaging (MRI), although dual-energy X-ray absorptiometry (DXA) appendicular lean mass (ALM) serves as an affordable and practical SM surrogate. Empirical equations, developed on relatively small and diverse samples, are now used to predict total body SM from ALM and other covariates; prediction models for extremity SM mass are lacking. The aim of the current study was to develop and validate total body, arm, and leg SM mass prediction equations based on a large sample (N = 475) of adults evaluated with whole-body MRI and DXA for SM and ALM, respectively. Initial models were fit using ordinary least squares stepwise selection procedures; covariates beyond extremity lean mass made only small contributions to the final models that were developed using Deming regression. All three developed final models (total, arm, and leg) had high R2s (0.88-0.93; all p < 0.001) and small root-mean square errors (1.74, 0.41, and 0.95 kg) with no bias in the validation sample (N = 95). The new total body SM prediction model (SM = 1.12 × ALM - 0.63) showed good performance, with some bias, against previously reported DXA-ALM prediction models. These new total body and extremity SM prediction models, developed and validated in a large sample, afford an important and practical opportunity to evaluate SM mass in research and clinical settings.

Body composition in patients with rheumatoid arthritis: a narrative literature review

There is growing interest in the alterations in body composition (BC) that accompany rheumatoid arthritis (RA). The purpose of this review is to (i) investigate how BC is currently measured in RA patients, (ii) describe alterations in body composition in RA patients and (iii) evaluate the effect on nutrition, physical training, and treatments; that is, corticosteroids and biologic Disease Modifying Anti-Rheumatic Disease (bDMARDs), on BC in RA patients. The primary-source literature for this review was acquired using PubMed, Scopus and Cochrane database searches for articles published up to March 2021. The Medical Subject Headings (MeSH) terms used were 'Arthritis, Rheumatoid', 'body composition', 'sarcopenia', 'obesity', 'cachexia', 'Absorptiometry, Photon' and 'Electric Impedance'. The titles and abstracts of all articles were reviewed for relevant subjects. Whole-BC measurements were usually performed using dual energy x-ray absorptiometry (DXA) to quantify lean- and fat-mass parameters. In RA patients, lean mass is lower and adiposity is higher than in healthy controls, both in men and women. The prevalence of abnormal BC conditions such as overfat, sarcopenia and sarcopenic obesity is significantly higher in RA patients than in healthy controls; these alterations in BC are observed even at an early stage of the disease. Data on the effect treatments on BC in RA patients are scarce. In the few studies published, (a) creatine supplementation and progressive resistance training induce a slight and temporary increase in lean mass, (b) exposure to corticosteroids induces a gain in fat mass and (c) tumour necrosis factor alpha (TNFα) inhibitors might be associated with a gain in fat mass, while tocilizumab might be associated with a gain in lean mass. The available data clearly demonstrate that alterations in BC occur in RA patients, but data on the effect of treatments, especially bDMARDs, are inconsistent and further studies are needed in this area.