Abstract
The present study leverages the comprehensive data from the National Health and Nutrition Examination Survey (NHANES) to examine the Influencing factors of sarcopenia (SA) and sarcopenic obesity (SO). The investigation is designed to a non-invasive, cost-effective, and convenient method that is applicable to the adult population, enabling the accurate and simultaneous detection of risks associated with SA and SO. Furthermore, this research will evaluate the critical values of effective anthropometric indicators, providing early warning for risk management in self-health care and offering valuable insights for subsequent research and clinical practice. The data pertaining to NHANES participants were meticulously selected from the databases of six cycles, spanning from 2001 to 2004 and 2011 to 2018. Utilizing the diagnostic criteria established by the American Foundation for the National Institutes of Health (FNIH), anthropometric measurement data were extracted to construct composite indices. These indices were then cross-referenced with diagnostic assessments from dual-energy X-ray absorptiometry and bioelectrical impedance analysis to examine the correlations between various metrics and the incidence of diseases. R software (version 4.3.3) was used for analysis, and the primary analytical methods employed included logistic regression, restricted cubic splines (RCS), and the Receiver Operating Characteristic (ROC) curve analysis (AUC). Sarcopenia and sarcopenic obesity are commonly observed in individuals within the middle-aged and elderly demographics. The prevalence of these conditions is higher among middle-aged men of a given age when contrasted with women at the age of 40. All anthropometric indexes demonstrated a positive correlation with the onset of SA and SO, with the association with waist-to-height ratio (WHtR) showcasing a heightened strength subsequent to the adjustment for all covariates. The predictive models of all ROC curves performed commendably, particularly with the body roundness index and WHtR forecasting models exhibiting superior performance, the area under the AUC curve is 0.87 (95 CI% 0.85, 0.88) and 0.86 (95 CI% 0.85, 0.88), respectively. The RCS curve delineated a distinctive J-shaped distribution for each physical index in concurrence with SA and SO, signifying an optimal value at which the incidence of these conditions is minimal; conversely, deviations from this optimal value entailed an escalated risk of disease. Diverse anthropometric index metrics bear a strong correlation with adult onset of sarcopenia and sarcopenic obesity, each displaying commendable predictive capability. Notably, the body roundness index and waist-to-height ratio may harbor heightened potential as indicative anthropometric indexes. Furthermore, the dose-effect relationship analysis inferred that the lowest disease risk is manifested among individuals with specific index profiles, thereby advocating for autonomous health monitoring to promote physical activity and bolster nutrient intake, thus mitigating the risk of sarcopenia and sarcopenic obesity.