Visceral Obesity-Related Indices in the Identification of Individuals with Metabolic Syndrome Among Different Ethnicities in Xinjiang, China.

BACKGROUND: Few studies have focused on the predictive ability of visceral obesity-related indices for metabolic syndrome (MetS), especially in different ethnic groups. This study aimed to evaluate the applicability of visceral obesity-related indices for MetS screening among three major ethnic groups living in remote rural areas of Xinjiang.
METHODS: Based on multistage stratified cluster random sampling method, 3,192 Uyghurs, 3,054 Kazakhs, and 3,658 Hans were recruited from Xinjiang, China. The Joint Interim Statement (JIS) criteria were used to define MetS. The receiver operating characteristic curve (ROC), area under the ROC curve (AUC), and predictive value of each visceral obesity-related index were used to evaluate the predictive ability of MetS.
RESULTS: After adjusting for potential confounding factors, the lipid accumulation product (LAP), Chinese visceral adiposity index (CVAI), waist-to-height ratio (WHtR), and atherogenic index of plasma (AIP) were significantly correlated with MetS for each ethnic group, and the odds ratios (ORs) for MetS increased across quartiles. LAP was best able to identify MetS status in Kazakhs (AUC=0.853) and Uyghurs (AUC=0.851), with optimal cut-offs being 36.3 and 28.2, respectively. Both LAP (AUC=0.798) and CVAI (AUC=0.791) most accurately identified MetS status in Hans, with the optimal cut-offs being 27.3 and 85.0, respectively. Moreover, the AUC of the combination of these visceral obesity-related indices is higher for each ethnic group. However, compared with LAP, the improved value of combined screening was not significant.
CONCLUSION: LAP had the best discriminative capability for the screening of MetS among Kazakhs, Uyghurs, and Hans. The screening ability of CVAI for MetS was similar to that of LAP in Hans. Thus, LAP may be a complementary indicator for assessing MetS in various ethnic groups.

Introduction

Metabolic syndrome (MetS) is becoming a major health concern in both developing and developed countries. With an increasing prevalence worldwide,1 it is a major risk factor for type 2 diabetes (T2DM) and morbidity and mortality from cardiovascular disease (CVD).2 Recently, the diagnostic criteria of MetS are non-stringent. For example, for women, the cut-off value of high-density lipoprotein cholesterol (HDL-C) has changed from <1.1 mmol/L in 2005 International Diabetes Federation (IDF) criteria3 to <1.3mmol/L in the 2009 Joint Interim Statement (JIS) criteria,4 whose purpose is to identify more patients at risk and facilitate primary prevention. Hence, early identification and treatment of individuals at high risk of MetS is imperative to prevent the adverse consequences related to its development.5 Unfortunately, it is still a challenge to identify individuals with MetS early due to the unobvious physical discomfort and complex diagnostic criteria associated with this disorder.

Recently, numerous studies reported that visceral obesity, compared to overall obesity, might be a better determinant of metabolic diseases, dyslipidemia, MetS, and CVD.6,7 It is particularly essential in Chinese individuals, who generally tend to have more visceral fat but lower body and subcutaneous fat than those in Western populations.8 Thus, early and accurate diagnosis of visceral obesity might be of crucial significance for the prevention of MetS. Although Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are gold standards to determine visceral fat, these are impractical to use for large-scale screening in underdeveloped areas. Therefore, several surrogate visceral obesity-related indices have been developed. One of the most well-accepted and widely used of these indices is the waist-to-height ratio (WHtR), which approximately reflects 52–81% of visceral fat.9 However, WHtR cannot distinguish between abdominal subcutaneous and visceral adipose tissue, and can not effectively improve the determination of visceral fat beyond using waist circumference (WC) alone.10 The lipid accumulation product (LAP), an index based on the combination of WC and serum triglycerides (TG), was proposed as a reliable marker of central lipid accumulation, and was more effective in identifying CVD risk compared to body mass index (BMI).11 Indeed, LAP has been reported as a useful index for detecting insulin resistance, non-alcoholic fatty liver, and MetS in various studies.12–14 Based on the differences in body fat distribution between the Chinese population and Caucasians,15 a new index called the Chinese visceral adiposity index (CVAI) was developed. This index combines age, BMI, WC, TG, and HDL-C, and was found to be a reliable indicator of visceral fat dysfunction.16 Further, the atherogenic index of plasma (AIP), a composite index based on TG and HDL-C,17 has been used as a reference to estimate abdominal obesity18 and is commonly used as an optimal indicator of the risks for atherosclerosis and coronary heart disease.19,20 However, no studies have systematically compared the value of these visceral obesity-related indicators (WHtR, LAP, CVAI, and AIP) for the screening of MetS. More importantly, pronounced differences in body fat distribution exist among various ethnicities.21 Nevertheless, to date, few studies have focused directly on different ethnic populations.

Xinjiang is a multi-ethnic region of China (containing 47 ethnic groups). Among them, the Kazakhs, Uyghurs, and Hans account for 92.4% of Xinjiang’s total population. In addition, most remote areas of Xinjiang are economically less developed compared with the remaining parts of China.22 Therefore, practical and effective indicators are urgently needed to screen MetS and other CVD risks. Thus, this multi-ethnic study was conducted to evaluate the feasibility of visceral obesity-related indices (ie, WHtR, LAP, CVAI, and AIP) for MetS screening among three ethnic populations (Kazakhs, Uyghurs, and Hans) living in rural areas of Xinjiang. Additionally, the present study also explored the optimal cut-offs for each indicator in different ethnic groups. The findings may provide a basis for the establishment and improvement of MetS screening and diagnostic strategies in Xinjiang and other areas of China.

Methods

Study Setting and Population

This Multi-ethnic Region Study was started in 2009 in Yili (Kazakhs), Shihezi city (Hans), Kashgar (Uyghurs), and Tumxuk (Uyghurs) of Xinjiang, which are nearly 2,800 miles away from Capital Beijing (As far as from the east coast to the west border of China). Multistage stratified random sampling method (prefecture-county-town-village) was adopted to recruit participants. First, Xinjiang was divided into South and North areas bound by Tianshan Mountain. Second, two representative prefectures were selected from the South (Kashgar and Tumxuk) and North (Shihezi and Yili), respectively, based on ethnicity, demographics, as well as economic and cultural status. Third, one county was randomly selected from each prefecture, and one town was randomly chosen in each county. Then, the corresponding villages in each town were selected using a stratified random sampling method. Finally, the local residents (aged ≥ 18 years) who had been living in the village for at least 6 months were randomly chosen and interviewed.

The exclusion criteria of the study subjects are as follows: (1) Those who can not complete the blood sample collection, questionnaire survey, physical examination, or blood pressure measurement, (2) People with disabilities or mental disorders, (3) People with serious illness, (4) Pregnant women, (5) Obesity caused by disease, (6) Obesity caused by taking certain drugs, (7) Those who have not signed the informed consent form.

A total of 11,419 participants were included in our analysis, with 1,390 and 125 individuals excluded due to missing laboratory and anthropometric data, respectively. The final analysis included 3,192 Kazakhs (mean age 49.8 years, male sex 42.1%), 3,054 Uyghurs (mean age 42.5 years, male sex 50.8%), and 3,658 Hans (mean age 44.3 years, male sex 39.4%) (Figure 1).

Figure 1

Flow chart of the multi-ethnic region study participants.

Assessment of MetS

The measurement of WC, systolic blood pressure (SBP), and diastolic blood pressure (DBP) were performed by health professionals following a standard protocol.23 After an overnight fast, blood samples were collected in the morning. All samples were delivered to a clinical laboratory for further analysis. Fasting blood glucose (FBG), plasma TG and HDL-C concentrations were measured using a biochemical auto-analyzer (Olympus AU 2700; Olympus Diagnostics, Hamburg, Germany). MetS was defined according to the joint interim statement of the IDF Task Force (JIS criteria), with recommended WC cut-offs for the Chinese population.4

Assessment of Visceral Obesity-Related Indices

The visceral obesity-related indices mentioned in the current study, including WHtR, LAP, CVAI and AIP, were calculated using the following equations:

- WHtR = WC (cm)/height (cm)

- LAP (men) = (WC (cm) - 65) × TG (mmol/L), or

LAP (women) = (WC (cm) - 58) × TG (mmol/L)11

- CVAI (men) = −267.93+0.68 * age+0.03 *BMI+4.00 *WC+22.00 *Log10TG−16.32 *HDL-C, or

CVAI (women) = −187.32+1.71 * age+4.23 *BMI+1.12 *WC+39.76 *Log10TG−11.66 *HDL-C16

- AIP = log (TG/HDL)24

Assessment of Other Covariates

The personal data of the participants were collected using structured questionnaires administered through face-to-face interviews. The questionnaire mainly inquired on demographics (age, sex, occupation, marriage status, etc.), lifestyle (eg, smoking status, alcohol consumption), and socioeconomic, dietary, and medical history.

Statistical Analysis

Continuous variables were described as means and standard deviations and were compared using Student’s t-tests. Categorical data were presented as frequencies and were analyzed with the Chi-square tests. Multinomial logistic regression was performed to determine the association between the visceral obesity-related indices and the risk of MetS. Each visceral obesity-related index was divided into increasing quartile groups to calculate the odds ratio (OR) and 95% confidence interval (CI) for MetS. To visualize the relationship between visceral obesity-related indices and the risk of MetS, the indicators of interest were also modeled as continuous variables using nomograms.

ROC analysis was applied to compare the ability of each indicator to screen for MetS, and the ROC curves were plotted for each of the indicators in Kazakhs, Uyghurs, and Hans, respectively. The overall screening accuracy was quantified using the AUC. An AUC of 0.5, 0.6 to < 0.7, 0.7 to < 0.8, 0.8 to < 0.9, and ≥ 0.9 corresponded to no discrimination, poor, acceptable, excellent, and outstanding discrimination, respectively.25 To reduce variance, a bootstrapping procedure was used 2000 times to validate the best AUC values and 95% CIs for MetS.26 Moreover, the comparisons of AUC values were performed using the method of DeLong et al27 and the optimal cut-off value was identified using the maximum value of Youden’s index, which is calculated by sensitivity (Sen) plus specificity (Spe) minus 1.

Statistical analyses were performed using SPSS version 23.0 (IBM Corp., Armonk, NY, USA), R software version 3.6.1 (, The R Foundation), and MedCalc statistical software version 15.2.2 (MedCalc Software bvba, Ostend, Belgium). Differences were considered statistically significant at a P-value < 0.05 (two-tailed).

Results

Basic Characteristics of Study Participants

A total of 3,192 Kazakhs (32.2%), 3,054 Uyghurs (30.8%), and 3,658 Hans (36.9%) were analyzed in this study. For each ethnic population, the MetS group showed significantly higher values for age, weight, WC, BMI, SBP, DBP, TG, FBG, LAP, CVAI, AIP, and WHtR, and lower values for HDL-C and height than those in the Non-MetS group (except for the height in Kazakhs, p=0.914) (Table 1).

Table 1

Basic Characteristics of the Study Participants

Variables	Kazakhs (n=3,192)				Uyghurs (n=3,054)				Hans (n=3,658)
	MetS Group	Non-MetS Group	t/χ2	p-value*	MetS Group	Non-MetS Group	t/χ2	p-value*	MetS Group	Non-MetS Group	t/χ2	p-value*
Gender (Men/Women)	422/534	921/1315	2.396	0.122	304/368	1247/1135	10.610	0.001	347/571	1094/1646	1.304	0.254
Age (years)	53.3±11.7	48.4±12.1	−10.48	<0.001	49.7±15.4	40.4±16.1	−13.308	<0.001	50.0±11.8	42.3±13.0	−15.827	<0.001
Height (cm)	162±8.70	162±8.12	0.108	0.914	159±8.84	160±8.43	3.012	0.003	162±8.81	163±8.62	2.493	0.013
Weight (kg)	69.1±10.5	63.0±10.4	−14.886	<0.001	61.6±11.0	57.0±9.51	−10.739	<0.001	70.1±13.0	62.4±11.4	−17.031	<0.001
WC (cm)	89.3±7.51	81.3±9.39	−23.309	<0.001	89.8±8.21	81.5±8.59	−22.187	<0.001	93.1±10.3	82.6±10.7	−25.61	<0.001
BMI (kg/m2)	26.2±3.07	23.9±3.11	−19.210	<0.001	24.3±3.48	22.2±3.00	−15.676	<0.001	26.5±4.23	23.3±3.64	−21.846	<0.001
SBP (mmHg)	136±20.9	122±18.1	−20.079	<0.001	136±19.6	120±17.4	−20.562	<0.001	142±24.7	124±21.8	−20.604	<0.001
DBP (mmHg)	89±11.9	80±10.8	−19.525	<0.001	84.6±12.2	75.6±12.0	−17.221	<0.001	91.2±14.5	79.8±13.3	−21.843	<0.001
TG (mmol/L)	1.97±0.78	1.25±0.65	−26.886	<0.001	1.65±0.66	1.03±0.48	−26.778	<0.001	1.47±0.77	1.01±0.56	−19.620	<0.001
HDL-C (mmol/L)	1.57±0.77	1.67±0.67	3.526	<0.001	1.02±0.22	1.17±0.27	13.606	<0.001	1.27±0.53	1.46±0.62	8.525	<0.001
FBG (mmol/L)	5.93±2.12	4.87±0.99	−19.243	<0.001	4.95±1.69	4.37±0.73	−12.903	<0.001	5.76±1.54	4.78±0.89	−23.612	<0.001
LAP	54.7±23.5	25.5±16.4	−40.186	<0.001	47.0±22.8	20.9±14.1	−36.332	<0.001	46.8±25.9	22.2±16.7	−33.208	<0.001
CVAI	109±30.9	71.4±37.6	−27.490	<0.001	106±37.5	60.1±40.0	−26.856	<0.001	112.7±43.7	63.0±44.6	−29.324	<0.001
AIP	0.10±0.25	−0.14±0.25	−25.559	<0.001	0.17±0.26	−0.10±0.30	−21.233	<0.001	−0.03±0.27	−0.19±0.28	−19.873	<0.001
WHtR	0.55±0.05	0.50±0.06	−23.623	<0.001	0.57±0.05	0.51±0.06	−22.570	<0.001	0.57±0.07	0.51±0.07	−26.456	<0.001

Note: *p-difference between MetS group and Non-MetS group.

Abbreviations: WC, waist circumference; BMI, body mass index; SBP, Systolic blood pressure; DBP, diastolic blood pressure; TG, triglycerides; HDL-C, High-density lipoprotein cholesterol; FBG, fasting blood glucose; LAP, lipid accumulation product; CVAI, Chinese visceral adiposity index; AIP, atherogenic index of plasma; WHtR, waist-to-height ratio.

Associations of Visceral Obesity-Related Indices with MetS

LAP, CVAI, AIP, and WHtR were strongly associated with MetS in three ethnicities after adjustment for potential confounders (age, sex, smoking and drinking habits, occupation, marital status, education, and BMI.) (p for trend<0.001) (Figure 2). For all variables of interest in Kazakhs and Uyghurs, the LAP indicated the highest OR value for MetS (3.751 for Kazakhs and 3.726 for Uyghurs), followed by CVAI (3.002 for Kazakhs and 3.042 for Uyghurs), AIP (2.597 for Kazakhs and 2.863 for Uyghurs) and WHtR (2.154 for Kazakhs and 2.225 for Uyghurs). On the other hand, the highest OR in Hans was for CVAI, followed by LAP, AIP, and WHtR (OR=2.672, 2.571, 2.229, and 2.162, respectively).

Figure 2

Adjusted odds ratios and 95% CI of MetS according to levels of visceral obesity-related indices for Kazakhs, Uyghurs and Hans, respectively (A) - Kazakhs, (B) - Uyghurs and (C) - Hans).

Using the Nomogram

For example, in Kazakhs, if the LAP level was 35, the point of 30 can be obtained from the points bar. Other variables can also be handled similarly. Presuming that the CVAI level of 60 had a point of 10, the AIP level of 0.2 was 70 points, and the WHtR level of 0.55 was 30 points. Then, the total score was 140 (30 + 10 + 70 +30). Finally, the risk of MetS was about 40% after marking a straight line from the total points to the risk axis (Figure 3).

Figure 3

Nomogram to estimate the risk of MetS for Kazakhs, Uyghurs and Hans (A) - Kazakhs, (B) - Uyghurs and (C) - Hans).

The ROC Analyses of MetS Screening

In Kazakhs, the LAP had the largest AUC value of 0.853 (95% CI: 0.840–0.865) among the four visceral obesity-related indices. The optimal cut-off point was 36.3 based on the maximum Youden’s index of 0.555 (Sen = 76.6%, Spe = 78.9%). In Uyghurs, the AUC values of LAP, CVAI, and AIP were all larger than 0.800. The LAP had the highest discriminative ability for MetS (AUC=0.851, 95% CI: 0.837–0.863), with the optimal cut-off point at 28.2 according to the maximum Youden’s index of 0.561 (Sen = 78.6%, Spe = 77.5%). The largest AUC for screening MetS in Hans was still observed for LAP (AUC = 0.798, Youden’s index = 0.454, Sen = 73.9%, Spe = 71.6% and optimal cut-off = 27.3) followed by CVAI (AUC = 0.791, Youden’s index = 0.463, Sen = 75.0%, Spe = 71.3% and optimal cut-off = 85.0). The ability of LAP and CVAI in screening for MetS were similar. In addition, for each ethnicity, when the four visceral obesity-related indices were combined, the diagnostic value for MetS was higher than that when taking the indices separately. Significant differences were detected between AUC values for all pairs of indices, except for the pair of LAP and CVAI in Hans. (Table 2 and Figure 4).

Table 2

The ROC Analysis of Each Visceral Obesity-Related Index and Nomogram for the Screening of MetS in Kazakhs, Uyghurs and Hans

Variables	Cut-Off	Sen %	Spe %	Youden’s Index	LR+	LR-	AUC (95% CI)	p-value*
Kazakhs
LAP	36.3	76.6	78.9	0.555	3.63	0.30	0.853 (0.840–0.865)	Ref
CVAI	83.2	81.8	63.6	0.454	2.25	0.29	0.788 (0.773–0.802)	<0.001
AIP	0.02	64.4	75.3	0.397	2.61	0.47	0.760 (0.745–0.775)	<0.001
WHtR	0.51	84.1	58.6	0.427	2.03	0.27	0.761 (0.746–0.776)	<0.001
Nomogram	0.26	81.5	76.3	0.577	3.43	0.24	0.863 (0.850–0.877)	<0.001
Uyghurs
LAP	28.2	78.6	77.5	0.561	3.49	0.28	0.851 (0.837–0.863)	Ref
CVAI	73.4	83.5	64.8	0.483	2.37	0.25	0.806 (0.791–0.819)	<0.001
AIP	0.07	71.4	75.9	0.473	2.96	0.38	0.805 (0.790–0.819)	<0.001
WHtR	0.51	85.1	57.8	0.430	2.02	0.26	0.771 (0.756–0.786)	<0.001
Nomogram	0.22	78.9	79.6	0.585	3.87	0.27	0.865 (0.849–0.881)	<0.001
Hans
LAP	27.3	73.9	71.6	0.454	2.60	0.37	0.798 (0.785–0.811)	Ref
CVAI	85.0	75.0	71.3	0.463	2.61	0.35	0.791 (0.778–0.804)	0.402
AIP	−0.10	70.6	63.4	0.340	1.93	0.46	0.716 (0.701–0.731)	<0.001
WHtR	0.52	80.6	61.0	0.416	2.07	0.32	0.770 (0.756–0.784)	0.001
Nomogram	0.30	67.8	82.0	0.498	3.77	0.39	0.830 (0.816–0.845)	<0.001

Notes: *p-difference between AUC values compared with LAP. Visceral obesity-related variables with maximum Youden’s index and largest AUC value in bold.

Abbreviations: Sen, sensitivity; Spe, specificity; LAP, lipid accumulation product; CVAI, Chinese visceral adiposity index; AIP, atherogenic index of plasma; WHtR, waist-to-height ratio; nomogram, the combined model of LAP, CVAI, AIP and WHtR.

Figure 4

ROC curves of each visceral obesity-related index for the screening of MetS in Kazakhs, Uyghurs and Hans according to the JIS criteria (A)- Kazakhs, (B)- Uyghurs and (C)- Hans).

Discussion

The present study showed that visceral obesity-related indices such as LAP and CVAI are accurate indicators in identifying MetS, with LAP being the index with the strongest diagnostic accuracy for MetS among all the three ethnic populations. This is the first large-scale population-based study to systematically evaluate the screening value of four visceral obesity-indices (LAP, CVAI, LAP, and WHtR) for identifying MetS in three ethnic populations in remote rural regions of China. The present study strengthened newly-found evidence that LAP is a simple and effective tool for screening MetS among different ethnicities, and will lay a foundation for the screening and diagnosis of other metabolic diseases.

There have been many studies focused on the prediction of MetS.28–30 However, it is clear that there are and will continue to be differences in body fat distribution among ethnic groups. For example, thresholds of BMI, WC, and WHtR have been recommended in several different ethnic groups and populations in World Health Organization guidelines.4,31 Despite these improved guidelines, one key question is whether the same criteria should be applied to someone of a particular country regardless of their subgroup ethnic. Various studies have additionally documented that the Chinese population also possesses subgroup ethnic variations. These need to be validated for various communities and ethnic groups.32,33 However, only little data on low-income areas in China are available due to reasons such as low priority of public health, poor medical services, transportation inconveniences, and language communication barriers in these areas. These gaps result in limitations in policy-making for public health in remote rural areas.

Evidence has shown that visceral obesity plays a central role in MetS and is an independent marker of cardiovascular risk, morbidity, and mortality.34,35 Since routine access to CT or MRI might not be feasible for many clinicians, these surrogate indices of visceral obesity are vital in screening for MetS. The present study revealed that there were significant relations between LAP, CVAI, AIP, as well as WHtR and MetS in all the three ethnicities after adjusting for confounding factors. Furthermore, the ORs of LAP were highest in both Kazakhs and Uyghurs, while CVAI indicated the highest OR in Hans when compared to the other three indices. This is explained by the fact that the CVAI is developed from Chinese Han adults, which may be more practical for the Chinese Han population. However, the risk for MetS when WHtR increased was not as significant compared to the other indicators in all Kazakhs, Uyghurs, and Hans. This may be due to the fact that WHtR can not accurately identify the origin of adipose tissue in the abdominal region.10

According to Hosmer and Lemeshow’s criteria,25 the present study found that LAP, CVAI, AIP, and WHtR were useful indices in screening for MetS (the AUC values were all greater than 0.7). This is in accord with the fact that visceral obesity-related indices might provide a broader evaluation of metabolic risk related to metabolic dysfunction and fat distribution.36 The LAP was an “excellent” index (AUC=0.853 for Kazakhs, AUC=0.851 for Uyghurs, and AUC=0.798 for Hans, almost close to 0.8). In all of Kazakhs, Uyghurs, and Hans, LAP was able to most accurately identify individuals with or without MetS compared to the other three indices. Consistent with previous studies,14,37 the findings of this study further highlighted the value of LAP in screening MetS across different diseases and ethnic groups. The combined presence of increased WC and TG levels has been associated with a high probability (around 80%) of increased visceral adipose tissue levels.38 These findings have been confirmed in other studies, deeming the so-called “hypertriglyceridemic waist” as a simple tool to screen for the presence of excess visceral adipose tissue.39 However, visceral obesity is a continuous process rather than a dichotomous one, while both WC and TG are single continuous variables are associated with metabolic risk.11 Thus, LAP is suggested to expand on the concept of the hypertriglyceridemic waist by providing a continuous risk marker that better reflects the excess lipid accumulation in visceral obesity and its related CVD risk.11 This related risk indicates the underlying continuous process which follows the over-accumulation of visceral adipose tissue, gradually promoting metabolic dysregulation, atherosclerosis, and low-grade inflammation.40

CVAI was reported to be a reliable index in predicting visceral adipose area and MetS in Chinese adults. The findings of this study were consistent with previous data regarding CVAI as a better marker of MetS in Hans.16 These results suggest that CVAI may be better than other visceral obesity indices at identifying MetS in the Chinese Han population. Interestingly, CVAI, which is developed on the basis of age, BMI, WC, TG, and HDL-C,16 includes more metabolic risk factors than those in the LAP,11 but the AUC values of CVAI were poorer than that of LAP in both Kazakhs and Uyghurs. Even in Hans, the AUC values of VAI and LAP did not differ statistically. It was further confirmed that LAP may be more accurate in screening for MetS in different ethnic groups.

AIP was another strong marker for predicting the risk of atherosclerosis and CVD24,41 and was more convenient and economical compared with B-mode ultrasound or CT. To date, few studies have evaluated the value of AIP for the screening of MetS. In agreement with a recent study,42 the present study showed that AIP was an “excellent” indicator for Uyghurs (AUC=0.805) and an “acceptable” indicator for both Kazakhs and Hans (AUC=0.760 and 0.716). However, AIP performed lower than LAP and CVAI, which may be due to the fact that AIP does not engage WC. Studies have shown that the combination of WC and AIP may increase their specificity and sensitivity for detection of visceral obesity in clinical practice.18 Thus, further studies are required to fully elucidate the screening value of AIP for MetS.

Furthermore, the values of these indices of interest for the screening of MetS in Hans were generally lower than that in Kazakhs or Uyghurs. Although the exact mechanism of these disparities remains to be elucidated, it could be, at least in part, due to the remarkable differences in adipose tissue distribution between Kazakhs, Uyghurs, and Hans. Kazakhs and Uyghurs may be more prone to have visceral adipose accumulation than that in Hans. In addition, this study also evaluated the value of combining the use of visceral obesity indices in screening for MetS, with results showing that the AUC values of combined screening for each ethnic group were higher than those when using the indices in isolation. However, compared with LAP, the improved value of combined screening was not significant (AUC: 0.863 vs 0.853 in Kazakhs, 0.865 vs 0.851 in Uyghurs, and 0.830 vs 0.798 in Hans, respectively).

Taken together, LAP may be of clinical applicability in detecting MetS in various ethnic groups. Until now, there is no official cut-off for LAP in screening for MetS. In this regard, the present study obtained optimal cut-offs of 36.3 for Kazakhs, 28.2 for Uyghurs, and 27.3 for Hans, respectively. These results differed from other similar studies, such as a study in Brazilian adults (34.2)14 and the Iranian population (49.7 for women and 39.9 for men),37 which may have been due to ethnic differences in environmental exposure and genetics. Moreover, the different MetS definitions may also contribute to the discrepancy in the optimal cut-off points. Although the sensitivity of LAP for the screening of MetS in each ethnic group was lower than that of CVAI and WHtR, the cut-off points of LAP indicated sensitivity and specificity values between 70% and 80% for all Kazakhs, Uyghurs, and Hans, thus moderately minimizing false-positive and false-negative cases.

Several limitations of the present study should be considered. First, its cross-sectional design limits the researchers from making causal inferences. Second, only four widely-used visceral obesity indices were analyzed in the study. There may be other novel indicators, which this study did not consider. Third, the MetS groups were not subdivided by sex. Therefore, further studies with prospective designs, more accurate indicators, and detailed information collection are needed to assess the screening value of visceral obesity-related indices in identifying individuals at high risk of MetS.

In conclusion, the present study investigated the screening ability of visceral obesity-related indices, including LAP, CVAI, AIP, and WHtR, in identifying MetS. LAP was the best index in identifying risk for MetS in all Kazakhs, Uyghurs, and Hans, with the optimal cut-offs being 36.3, 28.2, and 27.3 respectively. The screening ability of CVAI for MetS was similar to LAP in Hans, with the optimal cut-off being 85.0. LAP may be a complementary indicator for screening for MetS in various ethnic groups.