## 4 Discussion
This result is in agreement with the conclusion of a metanalysis about insulin resistance on women with PCOS, which concluded that BMI exacerbates insulin resistance in PCOS and has a disproportionately greater impact in PCOS than in controls [50]. Recently, it has been reported that the usefulness of the neck circumference is a good predictor for insulin resistance in women with PCOS [51]. Regarding bone mass, in our study, the higher percentages were associated with lower total cholesterol, lower LDL-c, and insulin resistance (HOMA). Lower HOMA-IR remained associated with PCOS regardless of bone mass. This means that both PCOS and bone mass are independent and opposite risk factors for higher HOMA, with the PCOS condition being the main risk factor when both coincide. It is unknown whether bone metabolism plays a pivotal role as mediator in atherosclerosis [52; 53] or whether bone loss is just a marker of systemic inflammation [54]. Other authors found an association between inflammatory markers, including insulin resistance, suggesting that a higher degree of inflammation might be in part responsible for the deterioration of bone health [55]. In our study, higher lean mass percentages predicted a better metabolic profile (lower TG and higher HDL-c), also modulated by the PCOS condition. This means that both PCOS and lean mass are independent and opposite risk factors for higher HOMA, with the PCOS condition being the main risk factor when both concur. Some authors are in agreement with this result, suggesting that the negative effect of fat mass on the metabolic risk could be counterbalanced by an increment of lean body mass and the net effect could be estimated by calculating the fat/lean body mass ratio [37; 56]. By contrast, [PERSON] et al. reported that an increase in lean mass in anovulatory PCOS appears to be associated with insulin resistance and TG levels [57]. Other authors also reported that lean mass correlated directly with HOMA independent of fat mass in women with PCOS [58; 59]. In addition, we analyzed the role of the women's age as a predictor of metabolic parameters. In our study, women's age was related to higher total cholesterol and LDL-c (regardless of body composition and independent of PCOS condition). Finally, we explored the influence of the PCOS condition (vs. control women) in the association of aging with metabolic disorders. We found worse metabolic parameters for women who suffer from PCOS. This is consistent with the fact that women with PCOS are more likely to develop long-term complications if they are obese, and these comorbidities increase exponentially and faster with age than in the general population [41; 60]. In conclusion, obesity in women with PCOS leads to worsening their endocrine, reproductive, and metabolic disturbances. It is important to analyze and offer accessible and reliable procedures to calculate fat mass and to diagnose its excess early. Previous studies analyzing fat mass and metabolic consequences used mainly expensive procedures not available in many settings (DEXA [27], bioelectrical impedance body composition analyzer [28], MRI, or CAT scan). In contrast, anthropometric assessment is a widely used, low-technology procedure. Skinfold caliper measurement as an indirect anthropometric technique is the most cost-effective method due to its validity and reliability with minimal equipment cost and technical training, enabling the estimation of whole-body fat. Our findings suggest that both body composition (measured by skinfeld thickness) and PCOS condition could predict metabolic disorders (especially insulin resistance) independently. Thus, offering easy and accessible ways to measure fat mass in different clinical areas could help to prevent obesity and its consequences.