In this study, we compared the associations of five anthropometric indices for T2DM among Chinese adults divided into four groups according to sex and age. Using survey data from a cross-sectional study of chronic diseases in Nantong city, east of China, we found strong evidence that there is a positive correlation between obesity-related measures and T2DM; a finding which was consistent with those of previous studies in China [15–16]. Previous studies have found that leptin level in obese people is higher than that in normal people, while adiponectin level is opposite. Leptin can activate renal sympathetic nerve and increase arterial pressure. Adiponectin can effectively protect cardiovascular system, which is negatively correlated with insulin resistance [24–25]. Obesity can lead to islet dysfunction and decrease of insulin secretion, meanwhile, adipocytes are insensitive to insulin, which leads to an increase of blood sugar [26].
The results of this study also show that, compared with other obesity indicators, WHtR had a greater impact on the risk of T2DM in the general population, which was consistent with previous research results. Previous studies have shown that height has an important influence on diabetes, while WC and WHR have not considered the influence of height [27–28]. In order to overcome this defect, most researchers used WHtR to study the relationship between overweight, obesity and chronic diseases [29–30]. WHtR is easy to calculate, and has a significant relationship with waist circumference without gender difference. Taking ≥ 0.5 as the cut-in point can well predict the risk of diabetes [31]. A study in China showed that waist-height ratio has no effect on impaired fasting blood glucose, but it is related to diabetes, which can be used as an important screening index for the elderly [32]. In addition, central and systemic obesity indices showed different correlations in different sex and age groups.
For males, WC had the highest OR and the largest AUC before after adjusting for confounding variables in both 18–59 and ≥ 60 age groups. The results of a meta-analysis of 16 cohort studies involving different ethnic groups in Asia showed that for every additional SD in BMI and WC, the risk of diabetes was 52% and 54%, respectively. WC was more closely related to diabetes [33]. A survey in China found that for every standard deviation increase in BMI and WC, the risk of diabetes increased by 53% and 64%, respectively. WC had a greater impact on the risk of diabetes [34]. The conclusions of these studies were the same as those in the present study, which might be related to the fact that insulin resistance is an important pathogenic factor for diabetes [35]. Studies have confirmed that insulin antagonism is more obvious in central obesity, and WC is recognized as an important indicator for measuring central obesity, which can better reflect insulin resistance [36]. Therefore, it was recommended that the waist circumference can be reduced through appropriate physical exercise and other means on the basis of weight control, thereby reducing the risk of type 2 diabetes.
However, among the females, WHtR and BMI tended to be the best predictors for T2DM in the 18–59 and ≥ 60 age groups, respectively. The reason for the sex difference in the relationship between obesity indicators and T2DM may be related to the sex difference in body fat distribution. Fat was mainly in the viscera in men and subcutaneous in women, which can provide evidence for gender differences. In thin Asian men with less subcutaneous fat, WC may be a better indicator of visceral obesity than BMI. Among thin Asian women, the impact of subcutaneous fat was greater than that of WC, and BMI may be more suitable for the indicator of overall fat and abdominal fat accumulation than WC [37–39]. On the other hand, compared with women, men were more stressed at work and slept less. Working pressure can increase the epinephrine secretion level of the body, and then lead to more fat into the abdomen [40]; Sleep deprivation was closely related to cardiovascular risk factors such as inflammatory markers in the blood circulation, and the resulting inflammatory response may be one of the mechanisms leading to metabolic diseases such as abdominal obesity and T2DM [41]. However, in recent years, Chinese women's rich diet nutrition, reduced exercise and increasing pressure at work have led to the increase of central obesity in young and middle-aged women [42]. This may explain why obesity indicators most closely associated with T2DM are inconsistent across age groups.
BAI was also included in this study as a new obesity index proposed in 2011, which was believed to be able to assess percent body fat more objectively based on hip circumference and height [43]. We found that BAI was positively associated with T2DM except in male ≥ 60 age group. The positive association of T2DM with BAI was not stronger than that observed in other generally used obesity indices. Consistently, the capacity of BAI in predicting T2DM was also found lower than BMI, WC and WHtR, which recognized as the most frequently used obesity indices. This was inconsistent with some American research results that BAI was superior to BMI [44–45], possibly because BAI was proposed by the research on hip circumference and height of African Americans and Mexican Americans [43], while the characteristics of height and hip circumference of Chinese Han people are quite different from them.
We also noticed that there was no positive association between WHR and T2DM in all sex and age groups. Therefore, using WHR as a weight predictor for T2DM was not recommended. This finding was similar to that of a study in Changchun. In that study, the cut-off value for WHR was not suitable for predicting T2DM compared with those of BMI and WHtR [19].
One of strengths in the present study was that we randomly selected a community-based population with a broad age range; this increases the generalizability of our results to local populations. Further, we compared the predictive values of five anthropometric indices (BMI, BAI, WC, WHR, and WHtR) to achieve accurate evaluation of T2DM prediction by obesity indicators for different age and sex groups. We believe that the findings of the present study may provide a reference for the selection of the appropriate anthropometric obesity indices for estimating the risk of T2DM in people of different sexes and ages.
Several limitations of the present study should be considered. Firstly, as a cross-sectional study, the causality between obesity indices and T2DM cannot be properly proven. Longitudinal follow-up studies need be conducted to further verify the results of the present study. Secondly, participants who reported T2DM by themselves may alter their lifestyle habits such as diet and exercise to skew their anthropometric indices. Although this was considered and adjusted for in the model and ROC curve analyses, information migration was unavoidable. Finally, only residents from a single area were recruited for this study. Therefore, the conclusions of this study may have some limitations in extrapolation due to the diet and lifestyle differences of different regions.