Obesity is a chronic, non-communicable condition in which body fat accumulates excessively and impairs physical and mental health, leading to lower quality of life and shorter life expectancy (11). In recent years, with the rapid economic development and the improvement of living standards, there have been great changes in dietary structure and lifestyle habits, physical activity and exercise have reduced gradually, and the incidence of obesity is increasing and is a serious health concern (12). The prevalence of hypertension, diabetes, and dyslipidaemia is increasing significantly worldwide (13–15). The prevention and treatment of obesity-related disorders is crucial, and health concerns, such as cardiovascular disease, have increased significantly. Serious cardiovascular events and related complications have affects the physical health of patients and places a heavy burden on families and society (16). Therefore, it is very important to diagnose obesity early on, and to take preventive measures to control and reduce the adverse consequences. It is thus necessary to develop simple, effective, and reliable screening criteria for early detection. At present, there are many diagnostic criteria for obesity, but these approaches are not uniform (17, 18). The present study selected ten existing obesity criteria to explore their correlation with body measurement indicators and their cut-off values, and investigate potential relationships with hypertension, diabetes, and dyslipidaemia.
Bioelectrical impedance, as a widely used method to measure human body composition, has been recognised in many medical circles. Self-monitoring with these simple, non-invasive body measurements will help control blood pressure, blood glucose, and blood lipids, thus further preventing the occurrence of cardiovascular diseases (19). This study showed that the anthropometric measures were higher in men than in women, and BMI showed no statistical significance differences between the two groups. This may be because the BMI method to evaluate the degree of obesity in the human body is based on height and weight. It is a quality indicator that can reflect the content of fat and muscle in the body to a certain extent, but it cannot distinguish the degree of influence of fat and muscle (8). The differences in other indicators between men and women were statistically significant, suggesting that gender may be discussed in the subsequent formulation of relevant cut-off values. TG showed no significant difference between the two groups. The evaluation indices of hypertension and diabetes were higher in men than in women, while the dyslipidaemia-related indices were higher in women than in men. This may be because of the study cohort composition, that is, a rural population from Northwest China, and smoking and alcohol consumption are higher in men, which causes many related diseases (20).
Based on the correlation between obesity criteria and anthropometric and biochemical variables, waist circumference has the most influence on all factors, and some studies show that the obesity of Chinese people is mainly abdominal obesity. Related studies have pointed out that abdominal obesity is characterised by abdominal fat accumulation, which is more closely related to cardiovascular risk factors than subcutaneous adipose tissue (21). Therefore, obesity indicators should be combined with those of abdominal obesity in order to monitor the health level of the population more comprehensively. BMI, AVI, and BRI have more correlation factors, indicating that these indicators are more likely to be affected by relevant anthropometric indicators, and they are also better correlated with these indicators. Biochemical variables have low correlation coefficients with obesity criteria, suggesting that these indices are not suitable for the evaluation of obesity-related indicators (22).
BF% can accurately reflect the body fat content, distinguishing whether an increase in body mass is due to fat or muscle, which is considered the gold standard for evaluating obesity. This study showed that the BF% in females was significantly higher than males, which may be related to the differences in physiological characteristics between the different sexes. Sex hormones are important factors involved in regulating fat storage, distribution, and decomposition in the body (23). WHtR had the largest AUC for predicting obesity in both sexes, followed by BMI and AVI. WHtR has a certain evaluation effect on hypertension and abnormal lipid metabolism in the participants, while AVI had the largest AUC for diabetes, and can be used in monitoring community health. WHtR is the most suitable index for reflecting body fat distribution and central obesity. Fat accumulation in the upper body is more likely to cause diabetes and hypertension than that accumulated in the lower body. Moreover, upper body fat may directly affect fatty acids and lipid metabolism throughout the body (24, 25). Although the BF% method is considered the gold standard for determining obesity, in view of the fact that the equipment for measuring body composition is generally expensive and not suitable for handling, it is inconvenient for practical application (26). The method of WHtR determining obesity is relatively simple, and is suitable for large-scale screening of the population.
This study investigated the cut-off values of different obesity indicators, which can be used as a reference for subsequent research. In order to make the evaluation objective and accurate, it is recommended to use multiple indicators for simultaneous evaluation. The use of a combination of indices is recommended when assessing obesity, together with the fat distribution, to increase the accuracy of predicting chronic cardiovascular disease. According to the status of each obesity diagnosis index, intervention to improve physical fitness and the quality of life is important (27–29).
Several limitations exist in our study. Dyslipidaemia included any group of dyslipidaemia components, but the specific dyslipidaemia components were not grouped in this study. The results are only applicable to the preliminary screening of dyslipidaemia in the community population. The data for this study is the baseline from a cohort study and contains an inner limitation of cause-and-effect analysis. Further investigation is necessary to confirm the findings of this study.