Association Among Abdominal Obesity Induces, Diabetic Retinopathy and Metabolic Syndrome in Community: a Cross-sectional Study

Background and aims: Obesity often coexists with diabetes has been recognized as a risk factor for diabetic complications. Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes, and the metabolic syndrome (MetS) is one of the most common symptoms of diabetes. The purpose of this study was to explore the relationship between DR and some induces, including NC, CVAI, PWNC and so on; as well as the relationship between DR and MetS. Methods: From 2018 to 2019, a total of 562 diabetics from the Hulan District of Harbin, Heilongjiang, were selected and completed a questionnaire survey. The questionnaire included basic patient information, anthropometric parameters, blood pressure, biochemical parameters and fundus photography results. Results: In both men and women, a one standard deviation (SD) increase in NC (cid:0) CVAI and PWNC was not associated with the prevalence of DR (P>0.05). However, in both men and women, a one SD increase in NC (cid:0) CVAI and PWNC was signicantly associated with the prevalence of MetS (P<0.05). These association were all adjusted for potential confounding factors. Moreover, DR was not associated with MetS(P>0.05). Conclusions: NC, CVAI and PWNC are associated with the prevalence of MetS. NC in men and CVAI in women had the largest area under the ROC curve compared to the other induces, which may be convenient and valuable anthropometric measurements for early prevention of MetS. However, these induces had no association with DR and there is no relationship between DR and MetS. Abbreviations: DR diabetic retinopathy, MetS metabolic syndrome, BMI body mass index, WC waist circumference, HC hip circumference, NC neck circumference, CVAI Chinese visceral adiposity index, WHR waist-to-hip ratio, PWNC product of WC and NC, FPG fasting plasma glucose, HbA1c glycated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, TG triglycerides, TC total cholesterol, UA uric acid, SBP systolic blood pressure, DBP diastolic blood pressure. glycated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, TG triglycerides, TC total cholesterol, UA uric acid, SBP systolic blood pressure, DBP diastolic blood pressure. metabolic BMI mass WC waist circumference, HC hip circumference, NC neck circumference, CVAI Chinese visceral adiposity index, WHR waist-to-hip ratio, PWNC product of WC and NC, FPG fasting plasma glucose, HbA1c glycated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, TG triglycerides, TC total cholesterol, UA uric acid, SBP systolic blood pressure, DBP diastolic pressure. Abbreviations: DR diabetic retinopathy, MetS metabolic syndrome, BMI body mass index, WC waist circumference, HC hip circumference, NC neck circumference, CVAI Chinese visceral adiposity index, WHR waist-to-hip ratio, PWNC product of WC and NC, FPG fasting plasma glucose, HbA1c glycated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, TG triglycerides, TC total cholesterol, UA uric acid, SBP systolic blood pressure, DBP diastolic blood pressure. Abbreviations: DR diabetic retinopathy, MetS metabolic syndrome, BMI body mass index, WC waist circumference, HC hip circumference, NC neck circumference, CVAI Chinese visceral adiposity index, WHR waist-to-hip ratio, PWNC product of WC and NC, FPG fasting plasma glucose, HbA1c glycated hemoglobin, HDL high-density lipoprotein, LDL low-density lipoprotein, TG triglycerides, TC total cholesterol, UA uric acid, SBP systolic blood pressure, DBP diastolic blood pressure.


Introduction
The global prevalence of diabetes is predicted to increase dramatically in the coming decades as the population grows and ages, in parallel with the rising burden of overweight and obesity, in both developed and developing countries 1 . About the epidemiological data, the worldwide prevalence of overweight and obesity has reached 33.3%, which has doubled since 1980 2 .
Moreover, DR is the most common microvascular complication in patients with diabetes and the leading cause of vision loss globally in working middle-aged adults 3 . And MetS is a cluster of obesity, hypertension, dysglycemia, dyslipidemia, and insulin resistance. Because hyperglycemia, oxidative stress and in ammation are the same processes involved in DR and MetS, several population studies evaluated its association with them. However, the relationship between metabolic syndrome and diabetic microvascular complications is contradictory and needs further study.
In fact, the methods to detect abdominal adiposity include dual-energy X-ray absorptiometry (DEXA), computed tomography (CT), magnetic resonance imaging (MRI) and dual bioelectrical impedance analysis (BIA). However, they are unsuitable for routine clinical practices in a general population on account of the radiation exposure, time requirements and high costs 4 . There are lots of induces to estimate obesity, such as neck circumference (NC), waist circumference (WC), body mass index (BMI) and the visceral adiposity index (VAI), the lipid accumulation product (LAP), which are calculated using the data of WC, BMI, triglycerides (TG), and high-density lipoprotein (HDL) 5 . Here we must mention two new indicators-Chinese visceral obesity index (CVAI), and the product of WC and NC (PWNC), which are considered to serve as a better predictor of T2DM and MetS in T2DM 6,7 .
The ndings of a cross-sectional study suggest that visceral adiposity is associated with DR in individuals with longstanding T2DM in Asia 8 . However, a study of 2016 found that, in Asian patients with T2DM, a higher BMI appeared to confer a protective effect on DR 9 . Therefore, the association between obesity and DR is equivocal. A new study has found that CVAI was not associated with DR in both men and women 4  TG(mmol/L)-11.66×HDL(mmol/L) Laboratory tests of fasting blood sample were performed using standard bio-chemical analysis methods, which included total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), and uric acid (UA), and using high pressure liquid phase detection method to test glycosylated hemoglobin A1c (HbA1c), and using chemiluminescence method to test fasting C-peptide.
In accordance with the guidelines for the prevention and treatment of T2DM in China (2020

Statistical analysis
Data analyses were performed with IBM SPSS Statistics, version 26. Continuous variables were expressed as the mean ± standard deviation (SD) or the median with an interquartile range (25%, 75%), and categorical variables were presented as percentages (%). The Student's t test and Chi-square test were used for continuous and dichotomous variables, respectively. Logistic regression tests were used to analyze the associations between abdominal obesity indices and DR or MetS. Data were summarized as odds ratios or regression coe cients (95% CI). Chi-square test was used to analyze the relationship between DR and MetS. The receiver operating characteristics (ROC) curve was constructed to evaluate the discrimination of different induces for MetS. The optimal cut-off point was determined by the maximum Youden index. A P-value < 0.05 (two-sided) was regarded as statistically signi cant.

Results
General characteristics of the diabetic participants Overall, 202 men and 360 women with diabetes were involved in the basal analyses. Among men, the prevalence of DR was 29.7%, and the prevalence of MetS was 84.2%. In women, the prevalence of DR was 37.8%, and the prevalence of MetS was 83.3%.
Respective characteristics of men and women by DR or MetS.
The clinical and biochemical characteristics of the subjects are shown in Tables 1 and 2. The participants were divided into two groups with or without DR, and with or without MetS. Compared with the men without DR, only CVAI was signi cantly higher in men with DR (P < 0.05). However, no differences in BMI, WC, HC, NC, WHR and PWNC were found between the two groups (P > 0.05). And BMI, WC, NC, WHR, CVAI and PWNC were all signi cantly higher in men with MetS (P < 0.05). Compared with the women without DR, only BMI was signi cantly higher in women with DR (P < 0.05). However, no differences in WC, HC, NC, WHR, CVAI and PWNC were found between the two groups (P > 0.05). And BMI, WC, HC, NC, WHR, CVAI and PWNC were all signi cantly higher in women with MetS (P < 0.05).  In addition, the participants were also divided into four groups according to the quartiles of NC (Tables 3  and 4). Both in men and women, BMI, NC, WC, HC, CVAI, SBP, DBP, and PWNC were all signi cant among groups (P < 0.05). However, MS was signi cant (P < 0.001) and DR was not signi cant among groups (P > 0.05).  Associations between abdominal obesity indices and prevalence of DR and MetS.
We found that in increased NC, CVAI, and PWNC were signi cantly associated with the prevalence of MetS both in men and women (Fig. 1). In men, a one SD increase in NC (OR 1.  (Fig. 1). Moreover, after adjusting for age, duration of diabetes, interventional time, and family history, in both men and women, a one SD increase in NC, CVAI, and PWNC was not associated with the prevalence of DR (all P for trend > 0.05) (Fig. 2).
We found that the diagnostic ability of abdominal obesity indices including BMI, WC, NC, WHR, CVAI and PWNC for MetS among men and women, respectively, analyzed by ROC curve. The differences between the area under the curve of CVAI and that of BMI, WC, NC, WHR, and PWNC for CVD and DKD both in men and women were all signi cant (P < 0.05). However, the differences between the area under the curve of these indices in DR were not signi cant (P > 0.05). CVAI had the largest area under the ROC curve compared to the other induces, and the cutoff with the biggest Youden index of CVAI was 109.01 with a sensitivity of 80.6% and a speci city of 78.7% (Fig. 3).

Discussion
Obesity due to poor diet and lifestyle habits is a time bomb for diabetes and its complications in the community population. As we all know, obesity frequently coexists with type 2 diabetes mellitus (T2DM), leading to the so-called "diabesity epidemic" 12 . However, the relationship between obesity and diabetes complications is ambiguous. A meta-analysis in 2018 (n = 14,575, 13 clinical studies) reported that obesity (assessed by BMI) signi cantly increased the risk of DR; this effect mainly referred to nonproliferative DR and to patients with T2DM, as shown in subgroup analysis 13 . Moreover, another crosssectional study (n = 1,414 DM patients) showed that abdominal obesity (assessed by WC) also correlated with DR 14 . Also, abdominal obesity (de ned by WHR) was positively related to mild-moderate and severe DR in T2DM women 9 . These results suggest that these induce may be associated with DR, however, our ndings showed that BMI, WC, NC, CVAI, WHR and PWNC were not associated with the prevalence of DR, which is consistent with the latest research 4 .
Evolving body of evidence suggests that the susceptibility to obesity-associated metabolic disorders is not mediated by the amount of fatness per se, but by the inability for excess energy to be stored appropriately in adipose tissue after reaching an individual's fat threshold 8 . Adipose tissue plays a pivotal role in storing excess nutrients, sensing nutrient status, and regulating energy mobilization. In the face of long-term excessive nutrition, exhaustion of adipose tissue expandability creates stress on adipocytes and elicits a transition from an adaptive to a maladaptive in ammatory response over time, leading to increased in ammation as characterized by deranged secretion of adipokines and proin ammatory cytokines, abnormal tissue remodeling and brosis, and eventually insulin resistance and its manifestations 15 . Visceral fat is closely related to in ammation and increased risk for metabolic disorders, whereas subcutaneous adiposity is comparatively less harmful 16 .
MetS is a cluster of obesity, hypertension, dysglycemia, dyslipidemia, and insulin resistance, which abdominal obesity and insulin resistance seem to play a central role in promoting the development of MetS 17,18 . MetS is a risk factor for cardiovascular complications of DM, but the association between MetS and microvascular complications of DM is limited. Moreover, the relationship between the components of metabolic syndrome and DR remains to be studied. NC has been considered a marker of upper body subcutaneous fat deposits and a simple and valuable screening tool for identifying individuals with obesity 5,19 , which is independently associated with MetS 19,20 . CVAI is a novel visceral adiposity index developed in Chinese adults that is associated with visceral fat area and insulin resistance 6,21 . And PWNC is a novel anthropometric index, as an obesity indicator for MetS 7 . In our study, we found NC, CVAI and PWNC were signi cantly associated with a greater prevalence of MetS. However, they were not associated with DR.
In addition, we also studied the differences among groups grouped by the cervical quartile. We found that NC, CVAI and PWNC are all signi cant among groups. These induces are all signi cant with MetS but not signi cant with DR. Moreover, NC had the largest area under the ROC curve in men, however, CVAI had the largest area under the ROC curve in women. This may be due to the uneven distribution of body fat between men and women. In men, the cutoff with the biggest Youden index of NC was 37.50cm, which has a higher speci city among these induces. And in women, the cutoff with the biggest Youden index of CVAI was 109.01, but the speci city of PWNC is higher than CVAI.
Hyperglycemia, oxidative stress, and in ammation are processes involved in MetS and DR, so several population studies evaluated its association with DR. A large multicenter clinic-based study from Italy reported an increased risk of type 2 diabetic retinopathy (T2DR) rather than type 1 diabetic retinopathy

Conclusions
The present study demonstrates that NC, CVAI and PWNC are associated with the prevalence of MetS. In men, NC may be a convenient and valuable anthropometric measurement for early prevention of MetS.
And in women, CVAI may be more suitable. However, these induces had no association with DR and there is no relationship between DR and MetS. Further prospective studies are necessary to examine our ndings in external populations.

Declarations
All the authors contributed signi cantly to the manuscript. Xin-Li conceived and designed the study, completed statistical analysis and wrote the manuscript. Zi-Wei Yu, Chang-Wei Yang and Ming Hao participated in data collection and collation. Hong-Yu Kuang, Yong Yu and Xu Peng contributed to the preparation of the study and critically reviewed the manuscript. Xin-Yuan Gao gave nal approval of the version to be submitted. All authors read and approved the nal manuscript.

Funding
This work was supported by grants from the Fund of Scienti c Research Innovation of the First A liated Hospital of Harbin Medical University (grant number 2020 M27, China).

Availability of data and materials
The data are available from the corresponding author upon reasonable request.
Ethics approval and consent to participate Not applicable.

Consent for publication
Not applicable.