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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 7  |  Issue : 2  |  Page : 40-46

Associated clinical factors of diabetic complications in Chinese patients with Type 2 diabetes


1 Center for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital, Capital Medical University, Beijing, China
2 Department of Adult Nursing, School of Nursing, Capital Medical University, Beijing, China

Date of Submission14-Dec-2021
Date of Decision25-Apr-2022
Date of Acceptance27-Apr-2022
Date of Web Publication30-Jun-2022

Correspondence Address:
Dong Zhao
Professor, Center for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital, Capital Medical University, 82, Xinhua South Road, Tongzhou District, Beijing
China
Meihua Ji
Associate Professor, School of Nursing, Capital Medical University, 10 Youanmen-Wai Xi-tou-tiao, Fengtai District, Beijing
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ed.ed_25_21

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  Abstract 


Background: The prevalence of the metabolic syndrome (MetS) is high among Chinese patients with type 2 diabetes. There is limited evidence in understanding the relationships between individual-level clinical indicators of MetS and diabetes complications among Chinese patients with Type 2 diabetes.
Aims and Objectives: This study described the characteristics of patients with Type 2 diabetes in terms of the prevalence of MetS and clinical factors related to the common diabetes complications.
Materials and Methods: Patients (n = 402) with Type 2 diabetes admitted to a tertiary hospital in Beijing were included in the study. Using patients' retrospective data, logistic regression was applied to determine the associated clinical factors of common diabetic complications.
Results: In this sample, the prevalence of MetS was 84.3%, with the prevalence of diabetic peripheral neuropathy, microvascular, and macrovascular complications being 59.7%, 63.4%, and 61.7%, respectively. Our results showed that the diastolic blood pressure was significantly associated with diabetic retinopathy, while the levels of C peptide and fasting glucose were significantly related to diabetic nephropathy. Meanwhile, the regression also showed that the waist to hip ratio (WHR) is a significant indicator for the development of macrovascular complications. A 0.1 increase in the WHR will increase the chances of having carotid artery disease by 1.29 folds.
Conclusion: The current study demonstrates that the prevalence of MetS and the common diabetic complications are relevantly high in this sample. Our findings suggest that reducing the WHR, controlling blood pressure, and improving glycemic control following clinical guidelines are essential to prevent or slow the progression of diabetes complications among patients with Type 2 diabetes.

Keywords: Diabetic management, metabolic syndrome, micro/macro vascular complication


How to cite this article:
Wang X, Zhao W, Ji M, Zhao D. Associated clinical factors of diabetic complications in Chinese patients with Type 2 diabetes. Environ Dis 2022;7:40-6

How to cite this URL:
Wang X, Zhao W, Ji M, Zhao D. Associated clinical factors of diabetic complications in Chinese patients with Type 2 diabetes. Environ Dis [serial online] 2022 [cited 2022 Aug 12];7:40-6. Available from: http://www.environmentmed.org/text.asp?2022/7/2/40/349539




  Introduction Top


Diabetes is a significant public health concern, and about 537 million adults are estimated to have diabetes globally.[1] In China, the prevalence of diabetes has increased rapidly over the past 40 years, from 0.67% in 1980 to 11.2% currently,[2] of which over 90% were reported with Type 2 diabetes. Metabolic syndrome (MetS) is a significant condition among patients with diabetes, which greatly increases the risk of developing cardiovascular disease.[3],[4] High prevalence of MetS has been identified among patients with Type 2 diabetes, ranging from 46% to 89%, according to different ethnic backgrounds.[5],[6],[7],[8] The definition of MetS often refers to a cluster of several conditions, including insulin resistance or diabetes, abdominal obesity, dyslipidemia or high cholesterol, and hypertension.[9],[10] Several criteria have been applied to identify the presence of MetS, and the criteria from the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) is one of the most widely and globally used guidelines.[6],[11],[12] According to the NCEP ATP III criteria for the Asian population,[11] MetS is confirmed when 3 or more of the 5 following features are present, including (1) waist circumference ≥90 cm in males or ≥80 cm in females; (2) systolic blood pressure ≥130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg, or currently on treatment/diagnosed for hypertension; (3) high-density lipoprotein (HDL) <1.03 mmol/L in males or <1.30 mmol/L in females; (4) Triglyceride (TG) ≥1.7 mmol/L or currently on treatment for dyslipidemia; (5) fasting glucose (FSG) ≥6.1 mmol/L (includes diabetes).

The prevalence of MetS among patients in China with Type 2 diabetes has been reported to be as high as 57.4% to 89.4%.[8],[12],[13] With an increased risk of MetS patients developing cardiovascular disease or having cardiovascular events, identifying MetS among Chinese patients with Type 2 diabetes is essential. If the metabolic control is not managed optimally in patients with Type 2 diabetes, complications associated with diabetes can even occur in the early stages and worsen as the disease progresses. Unfortunately, this may further complicate the management of diabetes and lead to blindness, renal disease, or cardiovascular disease, therefore negatively impacting patients' quality of life and reduced life expectancy.[1] Diabetic complications can be categorized into three groups: microvascular complications such as diabetic retinopathy (DR) and diabetic nephropathy (DN); macrovascular complications such as carotid and peripheral artery disease (PAD); and diabetic peripheral neuropathy (DPN).[1],[14] MetS has been identified as a risk indicator for microvascular and macrovascular complications among patients with diabetes.[15] Meanwhile, existing studies have demonstrated that hyperglycemia-related factors are associated with microvascular complications, and metabolic control-associated factors are more likely to be related to macrovascular complications among patients with Type 2 diabetes.[16],[17]

Clinical guidelines have suggested that lifestyle management is an essential strategy in controlling the progression of diabetes in patients, alongside necessary medication treatment.[18],[19] These guidelines have also emphasized the necessity of controlling patients' metabolic factors to slow and postpone the development and severity of diabetic complications. With the largest number of diabetic patients living in China,[1] increased attention should be given to those identified with Type 2 diabetes, especially those presenting with MetS, since more than 90% of diabetic Chinese patients have Type 2 diabetes.[20] However, there is limited evidence in understanding the relationships between individual-level clinical indicators (including anthropometric measures, lipid profile, glucose control, etc.) of MetS and diabetes complications among Chinese patients with Type 2 diabetes.

Purpose

Therefore, to better understand the characteristics of MetS and diabetic complications among Chinese patients with Type 2 diabetes, the current study aimed to examine the prevalence and clinical factors associated with common diabetes complications among Chinese patients with Type 2 diabetes.


  Methods Top


Study design and participants

This investigation was a retrospective study using patients' information retrieved from their medical records in September 2019. Eligible patients with Type 2 diabetes who were admitted to the Center for Endocrine Metabolism and Immune Disease at Luhe Hospital between January and June 2017 were included in the study. Information on patient's demographics, anthropometric measures, hyperglycemia-related factors (glycated haemoglobin [HbA1c], FSG, and C-peptide), lipid profile (cholesterol, TG, HDL, and low-density lipoprotein-(LDL) were collected by a research nurse.

Approval from the Ethics Committee of the study hospital was acquired before accessing patient data (#2019 LHKY 029-01). Inclusion criteria: diagnosis of Type 2 diabetes; both male and female. Exclusion criteria: severe mental and/or physical illness; being critically ill at admission; being pregnant. The medical record was accessed by the clinical research nurse who worked at the inpatient unit of the endocrinology center. A total of 614 patients with type 2 diabetes were admitted to the hospital between January and June 2017, with 11 patients identified as being critically ill or pregnant, and they were excluded from the study. The remaining 603 patients underwent initial data screening. For those admitted to the hospital more than once during the study period, the most recent values on study variables were used. Cases with missing values were excluded from the study since a large proportion (n = 201, 33.3%) of patients lacked data on the key variables such as the HbA1c, C-peptide, and the test results on related diabetic complications. Therefore, 402 patients were included in the final data analysis.

Measures

All patients' information was retrieved from the patient's medical records by the clinical research nurse at the study site. Variables related to patients' characteristics included patients' age, gender, height, weight, waist and hip circumferences, waist-hip ratio (WHR), body mass index (BMI), diabetes duration, smoking and drinking status, insulin use as well as their health history on existing hypertension and cardiovascular disease.

Clinical parameters

Hyperglycemia-related factors, including HbA1c and fasting plasma glucose, were used to evaluate how effectively the patients controlled their diabetes. The level of fasting C-peptide was also included to assess patients' level of insulin resistance and to determine the functional status of pancreatic beta cells. Test values related to cholesterol, TG, HDL, and LDL were included to assess the lipid profile among patients. MetS was determined using parameters related to blood pressure, TG, HDL, and waist circumference following the NCEP ATP III criteria for the Asian population.[11]

Diabetic complications

Diabetic peripheral neuropathy

The presence of DPN was evaluated based on the patients' clinical symptoms, health history, and test results such as ankle reflex, needle pinprick sensory test, and sympathetic skin response test following the China guideline.[21] Any reduced amplitude, the latency of N and P waves, significantly prolonged latencies, and area under the curve of sympathetic skin response would confirm the condition for DPN.

Microvascular complications

DR is one of the microvascular complications among patients with diabetes, which leads to blindness. DR was evaluated using the equipment (Topcon TRC. NW8) available at the center by an ophthalmologist based on the funduscopic findings. Findings were categorized into nonproliferative, mild, moderate, and severe nonproliferative DR and proliferative DR.[21],[22] If the patients were identified to have a cataract, they were recorded as a separate category. DN is another condition often associated with patients with Type 2 diabetes. DN was confirmed when the urinary albumin excretion rate was equal to or higher than 30 mg/24 h or has been confirmed by previous evidence.[23] The staging of the DR was established by following the guidelines for Chinese patients with Type 2 diabetes.[21] The estimated glomerular filtration rate was used to identify the stages of DR from Stage I to Stage V, with Stage V as renal failure following the guideline.

Macrovascular complications

Screening of the lower extremities' PAD was achieved using an ultrasound device and evaluated using the ankle-brachial index (ABI). PAD was confirmed when the ABI was <0.9. The grading of the PAD is termed stenosis (0.4<ABI <0.9), plaque (presence of plaque), occlusion and sclerosis (ABI >1.3),[21],[24] any presence of these indicators suggest the presence of PAD. A carotid ultrasound examination achieved screening for carotid artery disease (CAD). Based on the test result of carotid intima-media thickness, CAD was categorized into stenosis, plaque, occlusion, and sclerosis. Any presentation of these indicators warrants the existence of CAD.

Data analysis

Statistical Package for Social Science (SPSS, IBM Corp., Chicago, IL, USA) version 24 for Mac was used to conduct data analysis. The original data (n = 603) has a large proportion of missed values on various clinical outcomes, such as HbA1c and diabetes complication screening tests, and the missing pattern estimation suggested that they were not missing randomly (Little's MCAR test χ2 = 2162.951, df = 864, P < 0.001). Since these variables were the main study variables in the current study, patients (n = 201) with missing values on these variables were excluded. Therefore, 402 patients with complete data were included in the final analysis. However, this may introduce selection bias into the study as patients with missing data were excluded from the final analysis. Mean and standardized deviation were used to describe normally distributed continuous variables, and median and interquartile range were used to describe continuous variables that were not normally distributed. Proportions and frequencies were used to describe categorical variables. Individual diabetes complications (DPN, DR, DN, CAD, PAD) were dichotomized to reflect the absence or presence of the corresponding condition. Logistic regression was performed using the backward stepwise deletion approach after controlling patients' age, gender, duration of diabetes, existing hypertension and cardiovascular diseases, history of smoking and drinking, and the use of insulin (a total of eight covariates) to determine the associated clinical indicators for diabetic complications. A total of 11 clinical indicators, including patients' BMI, WHR, systolic and DBP, HbA1c, FSG level, C-peptide, and lipid profile, were tested to determine their effects on diabetic complications. The model was finalized to select the best-fitted model for explaining the outcome variables using P < 0.1 as the cut-off point for variables to be included in the final model. The odds ratio (OR) and Nagelkerke's R2 describe how many clinical indicators as a group explain the proportion of variation in diabetes complications. Researchers have suggested a preferable sample size of at least 400 in testing prediction models using logistic regression,[25] and we included 402 patients in the current study. Therefore, it is sufficient to test the significance. A priori of α < 0.05, with two-tailed tests, was set for significance testing.


  Results Top


Participant's characteristics

Participants' basic and clinical characteristics are described in [Table 1]. On average, patients were 56.3 (standard deviation [SD] = 14.4) years old and had diabetes for 9.3 years (SD = 7.5), with about half of patients being female (48.8%) and over 70.4% being overweight or obese. Of all patients, 55.2% and 19.4% of patients identified with existing hypertension and cardiovascular disease, respectively. The prevalence of MetS among these patients was 84.3%, with 59.7%, 63.4%, and 61.7% identified to have DPN, microvascular and macrovascular complications, respectively.
Table 1: Patient's demographics and clinical characteristics (n=402)

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Clinical factors associated with diabetes complications

Diabetic peripheral neuropathy

The final model examining the effects of clinical indicators on DPN was statistically significant, χ2 (10) = 122.10, P < 0.001, with 74.6% of the cases correctly classified. The model explained 35.4% of the variance for the DPN. As shown in [Table 2], the overall model identified that FSG and Cholesterol were two possible correlates for DPN. However, in this sample, they did not reach significance (with FSG assuming significance, P = 0.06).
Table 2: Associated clinical indicators for diabetic peripheral neuropathy (n=402)

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Microvascular complication

As shown in [Table 3], multiple logistic regression analyses were conducted to determine the clinical factors associated with DR and DN after controlling for eight covariates. In estimating the effect of 11 indicators on DR, the final model showed statistical significance, χ2 (11) = 97.21, P < 0.001, with DBP (OR = 1.03, 95% confidence interval [CI]: 1.01, 1.06, P = 0.02) remained significant in the model; the overall model roughly explained 28.7% of the total variance for the DR, and correctly classified 68.4% of the cases. As for DN, the overall model was also significant, χ2 (10) = 58.41, P < 0.001, with C-peptide (OR = 1.38, 95% CI: 1.03–1.84, P = 0.03) and FSG (OR = 1.05, 95% CI: 1.00–1.10, P = 0.05) were identified as significant correlates for DN in the model in which roughly 18.8% of the variance for DN was explained, and 69.4% of cases were correctly classified.
Table 3: Associated clinical indicators for microvascular complications (n=402)

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Macrovascular complications

After controlling covariates, [Table 4] displays the final models examining the effects of clinical indicators on PAD and CAD. The results showed that the overall model classified 69.2% of cases correctly, it was significant (χ2 (9) = 85.24, P < 0.001) and explained about 25.5% of the variance for PAD, with only TG remained in the model which did not reach significance (OR = 1.09, 95% CI: 0.99–1.20, P = 0.09). In addition, the final model for examining the effects of clinical indicators on CAD also showed significance (χ2[10] = 70.69, P < 0.001), in which the WHR (OR = 1.29, 95% CI: 1.03–1.63, P = 0.03) was a significant factor for CAD. The overall model explained 21.5% of the total variation for CAD and classified 66.9% of cases.
Table 4: Associated clinical indicators for macrovascular complications (n=402)

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  Discussion Top


This retrospective study investigated and described the prevalence of MetS and various diabetic complications among Chinese patients with Type 2 diabetes. We also examined the relationships between individual components of MetS and identified associated diabetic complications. Our results showed that the prevalence of MetS was 84.3%, and the prevalence of the most common diabetic complications ranged from 33.3% to 59.7% in this sample. In examining the associated factors for the development of microvascular complications, our results demonstrate that DBP remained significant for DR development. Likewise, FSG and C-peptide are significantly associated with the development of DN. Regarding macrovascular complications, WHR is identified as significantly associated with CAD development.

From this study, the prevalence of MetS was higher (84.3% vs. 57.4% and 72.5%) than in earlier studies among Chinese patients with Type 2 diabetes.[4],[12] Within our analyses, we considered the concurrent use of medications to treat hypertension and dyslipidemia in determining the status of MetS, following the criteria suggested by previous research.[11] This may have contributed to the relevantly high prevalence of MetS in our study. Previous investigations have suggested that high TG is a significant risk factor and high HDL is a protective factor for coronary artery disease.[26] This suggests that lifestyle changes in controlling body weight (especially reducing waist circumferences) and adopting healthy diet habits are essential in this patient group. Therefore, the inclusion of unsaturated fat, fibers with limitation of sugar intake, and necessary treatment should be encouraged among Chinese patients with Type 2 diabetes.

In the current study, 85.3% of patients reported at least one of the five diabetic complications, with DPN as the most commonly identified complication, followed by DR, CAD, PAD, and DN in hospitalized patients. Our result corroborates previous research in which a high prevalence of diabetic complications is consistently reported in China.[27] MetS has been identified to be associated with increased risks for developing cardiovascular disease, and it is a significant indicator for microvascular and macrovascular complications in patients with diabetes.[15] Although it is more meaningful to look at MetS as an integrative indicator when examining its relationship with diabetic complications, it is also essential to examine the associations between individual-level clinical indicators of MetS (hyperglycemic factors, metabolic indicators related to lipid profile, etc.) and the most common diabetic complications among patients with Type 2 diabetes.

Our study included the possible individual indicators of MetS in determining the correlates of significant diabetic complications in this sample. Following multiple logistic regression after controlling eight covariates, none of the individual clinical indicators remained significant in the model for DPN. Regarding the microvascular complications, the DBP was significantly associated with DR, while the C-peptide and FSG levels were significantly related to DN. Although HbA1c was not identified as a significant factor for any diabetic complications, our results are consistent with previous research in which hyperglycemia-related factors are more likely to be related to microvascular complications, along with a high level of C-peptide being associated with DN.[16] Meanwhile, in determining the individual indicators related to macrovascular complications, our results showed that WHR is significantly associated with the development of CAD. Furthermore, the chances of developing CAD increased by 29% with a 0.1 increase in WHR while all other variables remained constant. These findings suggest that modifying dietary habits and promoting physical activities, especially exercise of the abdomen, to control weight and reduce the WHR is essential to moderate the risks for the development of macrovascular complications, especially CAD.

Some notable strengths associated with this study may benefit future investigations. Notably, we examined a highly representative sample of diabetic complications (a total of 5 Types of complications) in a sample of Chinese patients with Type 2 diabetes. Additionally, this assessment included all individual-level clinical components of MetS. However, our study also has some recognized limitations. First of all, data were accessed retrospectively to determine the correlates of diabetic complications in this sample. Therefore it may not reflect the most current characteristics of Chinese patients with diabetes. Meanwhile, we cannot confirm a casual relationship between study variables and outcomes due to the current study design. Therefore, further longitudinal studies are needed to investigate their relationships. Secondly, selection bias might exist as the results were based on Chinese patients with Type 2 diabetes admitted to a tertiary hospital, and only those with complete data were included in the study. This limited the generalizability of the study findings to the general patient population and other ethnic groups.


  Conclusion Top


Our study showed that the prevalence of MetS and diabetic complications are relevantly high in Chinese patients with type 2 diabetes. The individual components of MetS associated with the most common diabetic complications are largely related to the WHR, blood pressure, and hyperglycemic related-factors. Our findings suggest that reducing the WHR, controlling blood pressure, and improving glycemic control following clinical guidelines are essential to prevent or slow the progression of diabetes complications among patients with Type 2 diabetes.

Implications

These results may assist clinicians in selecting specific strategies in routine practice and target patients with high risk for specific diabetic complications, therefore delaying and controlling disease progression. This evidence further confirms that healthcare providers and clinical researchers should emphasize the benefit of reducing the WHR among Chinese patients with Type 2 diabetes. The findings of our study will also inform nurses and other health professionals to develop tailored care to delay or prevent the progression of diabetes complications among Chinese patients with Type 2 diabetes.

Financial support and sponsorship

This work was supported by the National Natural Science Foundation of China, 81800723.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
International Diabetes Federation. IDF Diabetes Atlas. 10th ed. 2021. Available from: https://www.diabetesatlas.org. [Last accessed on 2021 Nov 10].  Back to cited text no. 1
    
2.
Li Y, Teng D, Shi X, Qin G, Qin Y, Quan H, et al. Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: National cross sectional study. BMJ 2020;369:m997.  Back to cited text no. 2
    
3.
Ginsberg HN, MacCallum PR. The obesity, metabolic syndrome, and type 2 diabetes mellitus pandemic: Part I. Increased cardiovascular disease risk and the importance of atherogenic dyslipidemia in persons with the metabolic syndrome and type 2 diabetes mellitus. J Cardiometab Syndr 2009;4:113-9.  Back to cited text no. 3
    
4.
Meifang Y, Xue S, Jue H, Yina TU, Jie HE, Yiming Z, et al. Metabolic syndrome increases Framingham risk score of patients with type 2 diabetes mellitus. Journal of Zhejiang University 2016;45:268-74.  Back to cited text no. 4
    
5.
Yadav D, Mahajan S, Subramanian SK, Bisen PS, Chung CH, Prasad GB. Prevalence of metabolic syndrome in type 2 diabetes mellitus using NCEP-ATPIII, IDF and WHO definition and its agreement in Gwalior Chambal region of Central India. Glob J Health Sci 2013;5:142-55.  Back to cited text no. 5
    
6.
Music M, Dervisevic A, Pepic E, Lepara O, Fajkic A, Ascic-Buturovic B, et al. Metabolic syndrome and serum liver enzymes level at patients with type 2 diabetes mellitus. Med Arch 2015;69:251-5.  Back to cited text no. 6
    
7.
Nsiah K, Shang VO, Boateng KA, Mensah FO. Prevalence of metabolic syndrome in type 2 diabetes mellitus patients. Int J Appl Basic Med Res 2015;5:133-8.  Back to cited text no. 7
    
8.
Ji M, Ren D, Gary-Webb TL, Dunbar-Jacob J, Erlen JA. Characterizing a sample of Chinese patients with type 2 diabetes and selected health outcomes. Diabetes Educ 2019;45:105-15.  Back to cited text no. 8
    
9.
Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Mech 2009;2:231-7.  Back to cited text no. 9
    
10.
International Diabetes Federation. The IDF Consensus Worldwide Definition of the Metabolic Syndrome. Belgium: International Diabetes Federation; 2006.  Back to cited text no. 10
    
11.
Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005;112:2735-52.  Back to cited text no. 11
    
12.
Jing Y, Hong T, Bi Y, Hu D, Chen G, Li J, et al. Prevalence, treatment patterns and control rates of metabolic syndrome in a Chinese diabetic population: China Cardiometabolic Registries 3B study. J Diabetes Investig 2018;9:789-98.  Back to cited text no. 12
    
13.
Li X, Cao C, Tang X, Yan X, Zhou H, Liu J, et al. Prevalence of metabolic syndrome and its determinants in newly-diagnosed adult-onset diabetes in China: A multi-center, cross-sectional survey. Front Endocrinol (Lausanne) 2019;10:661.  Back to cited text no. 13
    
14.
Jia W, Weng J, Zhu D, Ji L, Lu J, Zhou Z, et al. Standards of medical care for type 2 diabetes in China 2019. Diabetes Metab Res Rev 2019;35:e3158.  Back to cited text no. 14
    
15.
Lee MY, Hsiao PJ, Huang JC, Hsu WH, Chen SC, Shin SJ. Association between metabolic syndrome and microvascular and macrovascular disease in type 2 diabetic mellitus. Am J Med Sci 2018;355:342-9.  Back to cited text no. 15
    
16.
Gedebjerg A, Almdal TP, Berencsi K, Rungby J, Nielsen JS, Witte DR, et al. Prevalence of micro- and macrovascular diabetes complications at time of type 2 diabetes diagnosis and associated clinical characteristics: A cross-sectional baseline study of 6958 patients in the Danish DD2 cohort. J Diabetes Complications 2018;32:34-40.  Back to cited text no. 16
    
17.
Abdul-Ghani M, DeFronzo RA, Del Prato S, Chilton R, Singh R, Ryder RE. Cardiovascular disease and type 2 diabetes: Has the dawn of a new era arrived? Diabetes Care 2017;40:813-820.  Back to cited text no. 17
    
18.
International Diabetes Federation Guideline Development Group. Global guideline for type 2 diabetes. Diabetes Res Clin Pract 2014;104:1-52.  Back to cited text no. 18
    
19.
Beck J, Greenwood DA, Blanton L, Bollinger ST, Butcher MK, Condon JE, et al. 2017 National standards for diabetes self-management education and support. Diabetes Educ 2017;43:449-64.  Back to cited text no. 19
    
20.
Weng J, Ji L, Jia W, Lu J, Zhou Z, Zou D, et al. Standards of care for type 2 diabetes in China. Diabetes Metab Res Rev 2016;32:442-58.  Back to cited text no. 20
    
21.
Chinese Diabetes Society. China guideline for type 2 diabetes. Chin J Diabetes Mellitus 2014;6:447-98.  Back to cited text no. 21
    
22.
Fong DS, Aiello L, Gardner TW, King GL, Blankenship G, Cavallerano JD, et al. Retinopathy in diabetes. Diabetes Care 2004;27 Suppl 1:S84-7.  Back to cited text no. 22
    
23.
Gross JL, de Azevedo MJ, Silveiro SP, Canani LH, Caramori ML, Zelmanovitz T. Diabetic nephropathy: Diagnosis, prevention, and treatment. Diabetes Care 2005;28:164-76.  Back to cited text no. 23
    
24.
Khan TH, Farooqui FA, Niazi K. Critical review of the ankle brachial index. Curr Cardiol Rev 2008;4:101-6.  Back to cited text no. 24
    
25.
Bewick V, Cheek L, Ball J. Statistics review 14: Logistic regression. Crit Care 2005;9:112-8.  Back to cited text no. 25
    
26.
Ling Y, Jiang J, Wu B, Gao X. Serum triglyceride, high-density lipoprotein cholesterol, apolipoprotein B, and coronary heart disease in a Chinese population undergoing coronary angiography. J Clin Lipidol 2017;11:646-56.  Back to cited text no. 26
    
27.
Mao W, Yip CW, Chen W. Complications of diabetes in China: Health system and economic implications. BMC Public Health 2019;19:269.  Back to cited text no. 27
    



 
 
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  [Table 1], [Table 2], [Table 3], [Table 4]



 

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