The present study investigated the prospective association of BMI, WHtR and WC with cardiometabolic multimorbidity in a nationally representative cohort. Our results showed that BMI, WHtR and WC were all independently associated with increased risk of cardiometabolic multimorbidity among the middle-aged and elderly Chinese population. Moreover, compared with BMI, WHtR and WC exhibited better predictive utilities in future cardiometabolic multimorbidity.
Cardiometabolic multimorbidity, as a growing problem, poses a major challenge to health care systems throughout the world. Previous studies have suggested that cardiometabolic multimorbidity is much more harmful than a single cardiometabolic disease. For example, compared to the absence of any of the three cardiometabolic diseases, the hazard ratio (HR) for all-cause mortality was about twice in any one of these diseases, 4 times in any two of these diseases, and 7 times in the presence of all three diseases. In view of the serious harm of cardiometabolic multimorbidity, early predictive indicators need to be discovered urgently. However, quite limited studies have investigated the associations of easy-to access anthropometric indicators, such as BMI, WHtR and WC, with risk of cardiometabolic multimorbidity. To the best of our knowledge, there are only two studies exploring the link between BMI and cardiometabolic multimorbidity[7, 8]. The study by Kivimäki et al. involving 16 longitudinal research databases and 120,813 subjects suggested that the risk of cardiometabolic multimorbidity increased as BMI increased. This comprehensive analysis indicated that compared with healthy-weight individuals, overweight and obesity individuals (BMI ≥ 24) had twice the risk of developing cardiometabolic multimorbidity. The OR values between this study and ours are similar, indicating the predictive power of BMI. However, the Asian population has not been included in this study, and our study can be a supplement in this regard. Another study recruiting 8270 subjects showed that the hazard ratio for overweight/obesity was 1.19 times (95% CI: 1.00–1.43) higher for developing cardiometabolic multimorbidity from 1 baseline cardiometabolic disease than individuals with healthy weight.
WC, as an abdominal obesity measurement indicator, has been supported as an obesity-related health risk indicator for both Western and Asian populations[24–26]. Previous studies have suggested that WC has greater predictive power for risk of cardiometabolic diseases than BMI[9, 27]. Furthermore, a large amount of evidence has also supported that WHtR was more effective than BMI in predicting coronary heart disease, stroke and diabetes[9, 12–14, 21, 28, 29]. Remarkably, our study also found that WHtR and WC were independent predictors of cardiometabolic multimorbidity. Moreover, WHtR and WC were demonstrated to possess higher predictive abilities on risk of cardiometabolic multimorbidity than BMI in the current study. This phenomenon may be explained by the following reasons. First of all, BMI can only be used to measure the total body fat and cannot represent the body fat distribution. The susceptibility of cardiometabolic diseases may depend on the difference of regional body fat distribution and the ability of subcutaneous adipose tissue. Moreover, WC reflects body fat ratio more accurately than BMI, and it may play an important role in the early development of metabolic syndrome[32, 33]. A recent systematic review demonstrated that compared with BMI, WC increased the ability to discriminate adverse cardiometabolic risk outcomes by 3%. In addition, WHtR has been suggested to be less affected by race, age and gender and be relatively more stable[9, 11, 34]. People with the same BMI might have different risks of cardiometabolic diseases. Even among people with normal BMI, those with high WHtR are more likely to suffer from cardiometabolic diseases. Notably, about 35% of men and 14% of women with high WHtR would be missed if screened by BMI only, which could bring serious consequences for cardiometabolic disease prevention. Considering that WHtR and WC have better predictive power in cardiometabolic multimorbidity than BMI, screening by WHtR and WC might be applicable in future practice.
The exact mechanisms underlying the association between BMI, WHtR, WC, and cardiometabolic multimorbidity remain to be illuminated, but insulin resistance and ectopic fat deposition may be the main contributors. Adipose tissue produces a large amount of bioactive mediators, which leads to insulin resistance. Insulin resistance may cause cardiometabolic diseases in the following ways. First, in a state of insulin resistance, inflammation occurs in the body, which eventually leads to atherosclerosis. Second, insulin resistance affects the production of apolipoprotein A1 (apoA-Ⅰ) or the liver secretion of high-density lipoprotein (HDL), which could be a trigger for metabolic syndrome. Third, insulin resistance would obstruct normal heart function through inhibiting metabolic pathways and over-stimulating growth factors. In addition, ectopic fat deposition triggers a pathological metabolic response, increasing the risk of metabolic diseases. Excess free fatty acids are produced outside the fat storage tissue, and transferred to ectopic sites, including the viscera, heart, and vasculature, ultimately leading to cardiometabolic diseases.
There are several merits in this study. Our study is the first to investigate the association of WHtR and WC with risk of cardiometabolic multimorbidity. Moreover, WHtR and WC were shown to be advantageous in predicting cardiometabolic multimorbidity than BMI. In addition, the two-stage strategy to assess cardiometabolic multimorbidity could provide mutual validation and increase the reliability of the associations. Limitations should be noted as well. First, our research was based on the four-year follow-up data, preventing the assessments of a long-term association. Second, the cardiometabolic diseases included in this study were self-reported. However, self-reported cardiometabolic diseases have been proved to be highly reliable in large-scale epidemiological studies.