We investigated the association of various anthropometric measures with all-cause and cause-specific mortality in a large, nationally representative cohort of U.S. adults with up to 11.3 years of follow-up. We found that BMI and WHtR were positively correlated with mortality risk. The association between BMI and mortality was inverted J-shaped, whereas the association between WHtR and mortality was positive J-shaped. Although other anthropometric indicators of overall obesity also suggest a negative association between obesity and mortality, none of the core obesity indicators supported such a counterintuitive relationship. Ta. The results of the current study suggest that the obesity paradox may be an anthropometric outcome, with central body mass index independently and positively associated with all-cause mortality, cardiovascular mortality, and non-cancer mortality. This suggests that the obesity paradox may be an influence. Exists.

The obesity-survival paradox has been previously reported in studies in critically ill patients, the elderly, and the general population. [8-10]. A meta-analysis of 218,532 patients with cardiovascular disease also demonstrated that overweight and obese patients had lower overall mortality than normal-weight patients, with a hazard ratio of approximately 0.70. [19]. Using BMI as an anthropometric index, we reproduced this counterintuitive association in an inverted J-shaped pattern. This resulted in the risk of death gradually decreasing within the initial unit of BMI and then reaching a plateau. The lowest risk of death was all within the overweight range, and higher BMI further increased the chance of protection for survival. Furthermore, when we examined other indicators of overall obesity, the results were similar to those for BMI, indicating that overall body mass index derived from weight-based calculations is consistent in estimating mortality risk. suggests.

Previous findings on the association between central body mass index and adverse outcomes are heterogeneous, with some studies reporting a J-shaped or monotonic positive association and others reporting a negative or null association. There were also studies showing that. [20,21,22,22]. Methodologically, some of these studies did not address the hard endpoint of mortality; others focused on all-cause mortality and lacked data on cause-specific mortality; Some analyzed only a single anthropometric indicator. Our results provide evidence regarding these open questions. We found a positive J-shaped association between WHtR and all-cause mortality, cardiovascular mortality, and other-cause mortality, independent of BMI. The risk inflection point occurred around WHtR 0.6, just above the currently recommended threshold of 0.5, with mortality risk changing slightly up to the inflection point and then increasing rapidly and linearly. This pattern of positive associations was also consistently observed for other anthropometric indices of central obesity, such as waist circumference, BRI, WWI, RFM, and BSI, although it was slightly reduced for RFM and BSI. The current findings are consistent with the results of recent large studies that revealed an independent positive association between central body mass index and adverse outcomes (e.g., early mortality, heart failure hospitalization, cardiometabolic risk). Some of them used Mendelian randomization designs to infer causal relationships. [23,24,25]. No substantial association was found between WHtR and cancer mortality. The association between obesity and cancer incidence and mortality varies by cancer site. The International Agency for Research on Cancer (IARC) found strong evidence of a dose-response relationship with obesity, including cancers of the esophagus, colorectal, pancreas, cardia, liver, gallbladder, and kidney. reported seven cancers. [26]. However, the three most common cancers in the current cohort were breast cancer (15.4%), prostate cancer (15.3%), and skin cancer (14.8%), accounting for almost half of cancer patients . This may explain our failure to find a clear association between obesity and cancer mortality in this nationally representative population.

The wide variety of association patterns may be due to differences in population-level risk classification using different anthropometric measures. In the present study, despite the strong linear correlation between BMI and WHtR, normal weight individuals were significantly reclassified after considering WHtR. Only half of normal weight individuals are within the normal range of WHtR, suggesting that the pathophysiological environment of the other half may be overlooked. Misclassification of overweight or obese individuals was low, with 98% having a WHtR greater than 0.5. A small number of people who are overweight or obese have normal WHtR, but this may be due to increased muscle mass rather than fat accumulation. These individuals, known as metabolically healthy obese (MHO), have been previously documented. [27]. Our findings suggest that BMI is not sufficient to identify the high-risk phenotype of central obesity defined by WHtR, especially in normal-weight individuals (underestimation of risk). Current evidence suggests that high-risk characteristics for central obesity include a high ratio of visceral to subcutaneous adipose tissue, large waist circumference, and a high ratio of waist circumference to hip or leg circumference. is also shown to be included. [28]can be captured by central body mass index rather than BMI alone.

Epidemiological and genetic evidence indicates that the regional distribution of fat may be more important than the absolute amount of fat in predicting obesity-related metabolic risk. [14, 25, 29]. Computed tomography (CT) and magnetic resonance imaging (MRI) allow precise quantification of body composition at each level, thereby determining subcutaneous adipose tissue (e.g. gluteal and femoral fat) and VAT (e.g. : intra-abdominal fat and ectopic fat) can be identified. [30, 31]. However, CT involves ionizing radiation and MRI is time consuming, both are expensive and require specially trained personnel to perform. DXA serves as a viable alternative with low radiation exposure and cost, and it has been validated by CT and MRI in identifying high-risk metabolic phenotypes. [32, 33]. We found a moderate correlation between DXA-based anthropometric indicators and VAT measurements. This is consistent with the expectation that anthropometric indicators can only provide rough estimates of fat distribution. Specifically, WHtR and waist circumference had stronger correlations with her VAT measurements than BMI, while weight had the weakest correlation, and the correlation coefficients were consistent with previous studies. [32]. Mechanistically, subcutaneous adipose tissue plays an important role in energy storage and thermoregulation, and when its storage capacity is saturated, lipotoxic she-VAT deposition occurs. VAT exerts its biological effects on adipocytes through increased secretion of pro-inflammatory adipokines and decreased secretion of anti-inflammatory adipocytokines. [2, 34]. As a result, VAT creates an atherogenic, diabetic, and inflammatory environment that leads to downstream metabolic dysregulation and cardiovascular damage. [35]. As routine measurement of VAT may be impractical, the use of alternative anthropometric indicators as simple estimates in clinical practice is promising. The stronger correlation between WHtR and VAT measurements compared to BMI may partly explain why WHtR provides a better estimate of adverse outcomes.

The growing obesity epidemic is leading to significant increases in mortality, morbidity, and health care costs. Therefore, obesity is included in the global goal to control non-communicable diseases (NCDs). [36]. Based on current research, there are several considerations. First, it is essential to implement a comprehensive and effective prevention strategy that focuses on promoting a healthy lifestyle and controlling excessive weight gain. However, the existence of the obesity-survival paradox can cause confusion and hesitation among the public and policy makers. Our findings suggest that the obesity paradox may be an anthropometric outcome rather than an actual biological benefit from excess fat storage, suggesting that being overweight or obese may be associated with normal weight This eliminates concerns about improving survival rates. Second, susceptibility to obesity-related metabolic risks may be mediated by visceral fat, and anthropometric measurements of central obesity provide additional, independent information other than BMI in characterizing adverse risks . A growing number of obesity societies are recommending the routine use of central body mass index (waist circumference or WHtR) alongside BMI for obesity stratification and management. [15, 37]. Third, to accurately assess obesity, the validity, feasibility, and standardization of assessment metrics must be considered. Measuring only your waist circumference is not enough. This is because the effect of height is not taken into account. The effect of height is strongly inversely correlated with health risks such as cardiovascular disease and cancer. [38, 39]. Waist-hip ratio is a useful metric to consider both VAT and subcutaneous adipose tissue in the lower body. However, hip circumference is difficult to obtain, so waist-to-hip ratio is not very practical. WHtR corrects waist circumference according to height, regardless of gender, age, or ethnicity, and normalizes the threshold to 0.5. This simplifies the health message that waist circumference should not exceed half your height, providing a more attainable and practical measure for both medical professionals and the general population. Finally, further research will explore whether the adoption of these anthropometric indicators can meaningfully enhance risk prediction algorithms beyond traditional measurements, and whether these anthropometric indicators can serve as valid targets for risk reduction. You need to focus on what.