The findings of this study demonstrate that the CC/BMI exhibits superior sensitivity and positive predictive value compared to calf circumference adjusted for BMI, confirming its efficacy in identifying sarcopenic obesity. Specifically, the study yielded an AUC of 0.850, with a sensitivity of 81.63% and a negative predictive value of 95.1% for a CC/BMI ≤ 1.20. Early detection of sarcopenic obesity is essential, as it enables timely interventions to reduce the associated risks of disability and mortality.
Furthermore, the significant correlations between the CC/BMI and key clinical parameters such as handgrip strength and gait speed underscore its broader clinical relevance. These findings suggest that the CC/BMI is not only a robust marker of sarcopenic obesity but also a valuable indicator of musculoskeletal health and functional capacity, both of which are crucial determinants of quality of life in older adults.
By contrast, the method of adjusting calf circumference for BMI demonstrated weaker predictive performance, with an AUC of 0.672 and a sensitivity of 60.2%. This suggests that BMI-based adjustments may inadequately account for variations in muscle mass, adiposity, and body composition, particularly in the elderly. The superior discriminative ability of the CC/BMI is likely attributable to its incorporation of both fat and muscle parameters.
Recent studies have shown that sarcopenic obesity is associated with hyperglycaemia, hypertension, dyslipidemia, insulin resistance and an elevated cardiovascular risk profile [3, 17]. In our study, the prevalence of hypertension and cardiovascular disease was notably higher in the sarcopenic obese group, consisting with the existing literature [2].
There are several recommended screening methods for sarcopenic obesity. According to the Consensus Statement by the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO), screening should include surrogate parameters for sarcopenia (such as clinical symptoms, clinical suspicion, or questionnaires like SARC-F in older adults), alongside increased BMI or waist circumference. These measurements should be determined using ethnicity-specific thresholds, and patients meeting both criteria should proceed to the diagnostic stage [1].
Despite the availability of multiple screening methods for sarcopenic obesity, each has notable limitations. Varying cut-off points for BMI and waist circumference have been proposed, with differences influenced by ethnicity, the presence of comorbid conditions such as hypertension and dyslipidemia, and mortality risk assessments. Establishing standardized reference ranges for different racial or ethnic groups remains a challenge. For instance, the World Health Organization (WHO) defines obesity as a BMI ≥ 30 kg/m² due to its association with increased mortality risk [18]. However, BMI alone may not accurately reflect obesity prevalence, as studies have shown it often underestimates body fat when compared to direct measurement methods, such as dual-energy X-ray absorptiometry (DEXA). Furthermore, its diagnostic accuracy decreases with advancing age in both men and women, evidenced by declining concordance indices [19, 20]. It is important to note that body composition can change significantly even when BMI remains within a certain range. For example, an individual may have a BMI and/or waist circumference within the normal range, but have increased adipose tissue and decreased muscle mass, resulting in sarcopenic obesity [20, 21].
Screening for sarcopenic obesity requires clinical suspicion based on factors such as advanced age, chronic inflammatory or endocrine diseases, recent hospitalization, surgery, immobility, and rapid weight changes [1]. Clinical signs and symptoms can be misleading in sarcopenia screening because they are often non-specific. Although questionnaires like the SARC-F are commonly used to screening sarcopenia, their sensitivity is often inadequate, as demonstrated by a sensitivity of only 29.5% [22]. The modified SARC-Calf questionnaire improves sensitivity by incorporating calf circumference, yet its role in detecting sarcopenic obesity remains unclear [1, 23].
Calf circumference is another anthropometric measurement for sarcopenia screening, with population-specific cut-offs has already been established also in our country. However, the cut-off value for predicting sarcopenia in obese individuals remains unknown. Recently, the utility of calf circumference in patients with obesity has garnered significant attention. A recent study proposed using adjusted calf circumference, which is calculated by adding 4 cm for individuals with a BMI of less than 18.5 or subtracting 3 cm, 7 cm, or 12 cm for those with a BMI of 25–29, 30–39, and 40 or above, respectively, from the initial calf circumference measurement [7]. This adjustment suggests that calf circumference, when modified for BMI, may correlate better with low muscle mass as determined by DEXA. However, the sensitivity of BMI-adjusted calf circumference in predicting sarcopenic obesity has not yet been tested.
Recognizing the limitations of current screening methods is crucial, as these approaches impact clinical decision-making [23].
The findings of our study suggest that the CC/BMI is an effective method for screening sarcopenic obesity, demonstrating notable efficacy compared to calf circumference adjusted for BMI. This method can be implemented without the need for specialized equipment or extensive training, making it easily integrable into the standard geriatric assessment process. Utilizing the CC/BMI in clinical practice may facilitate early intervention and ultimately enhance the health and functional status of older adults at risk of sarcopenic obesity.
There are several notable strengths of this study. To the best of our knowledge, this is the first study to introduce the CC/BMI as a practical and innovative anthropometric tool for detecting sarcopenic obesity and offers a simple, non-invasive, and cost-effective screening option. The use of ultrasound-derived anterior thigh muscle thickness and the STAR index add objective and reliable measures of muscle mass, enhancing the accuracy of sarcopenia diagnosis. The inclusion of multiple parameters, such as handgrip strength and walking speed, and the scales of daily living activities allows for a more holistic evaluation of sarcopenic obesity, further strengthening the study’s methodology and relevance to clinical practice. Additionally, by comparing the CC/BMI to calf circumference adjusted for BMI, the study provides valuable insight into the relative effectiveness of different methods for detecting sarcopenic obesity, showing that CC/BMI has superior predictive capability.
However, the study also has limitations. The study was conducted in a geriatrics outpatient clinic, which may limit the generalizability of the findings to other populations or settings, such as community-dwelling older adults or those in institutionalized care. Exclusion of individuals with advanced dementia, neurodegenerative diseases, and other conditions may result in a healthier study cohort, limiting the applicability of findings to more frail or diverse populations. To gain a more comprehensive understanding, future research should include diverse populations from multiple centres and regions. In addition, an increase in BMI does not always mean an increase in fat tissue. The inability to assess body fat is one of the limitations of our study.
Another limitation of our study is the use of grip strength cut-off values specific to the Turkish population. While these values were developed and validated based on a large cohort from Türkiye and are relevant for internal consistency and clinical applicability within this context, they may limit the external validity of our findings. The use of population-specific thresholds may reduce the generalizability of our results to other ethnic or regional groups. To address this, we performed an additional analysis using the European Working Group on Sarcopenia in Older People (EWGSOP2) cut-off values, which yielded similar predictive accuracy for sarcopenic obesity, further supporting the robustness of our findings. Nevertheless, further studies using internationally accepted cut-off values across diverse populations are necessary to validate the applicability of our results in broader contexts.
One important limitation of our study is the lack of direct measurements of fat mass and fat-free mass (FFM), which are considered more accurate indicators for assessing body composition and diagnosing obesity. Although we observed the coexistence of low muscle mass and obesity—potentially suggesting an increased fat mass relative to FFM—this could not be confirmed in the absence of objective body composition analyses. Therefore, the lack of fat mass and FFM data may have limited the accuracy of our findings related to sarcopenic obesity. Future studies incorporating direct measurements of body composition are warranted to validate and expand upon our results.
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