Literature DB >> 36158357

High Fasting Blood Sugar and Increased Waist Circumference as Risk Factors for Diabetic Retinopathy in Type 2 Diabetes Patients Older than 45 Years.

Rangabashyam Seetharaman Ranganathan1, Ezhil Vendhan K2, Shanmugasundaram R1, Nivya Manimozhian3.   

Abstract

Introduction Diabetes mellitus (DM) has a long-term impact on retinal micro-blood vessels, culminating in the progression of diabetic retinopathy (DR); however; screening for DR is not widely used due to a lack of accessibility and economic constraints, especially in resource-limited settings. Thus, a longitudinal marker that is associated with the development of DR is required. This study sought to assess the association of DR with fasting blood sugar (FBS) levels and waist circumference. Methodology A cross-sectional study was conducted in a tertiary care hospital for one year. All individuals diagnosed with Type 2 DM (T2DM) and ≥45 years of age were included in the study. Individuals with fasting blood glucose levels of <126 mg/dl and <3 years of diagnosis with T2DM were excluded from the study. Individuals having one or more retinal microaneurysms or retinal blot hemorrhages, with or without any additional abnormalities, were diagnosed with DR. The results were analyzed using SPSS version 21 (IBM Corp., Armonk, NY). Results The prevalence of diabetic retinopathy among the study participants was 67.6 %. There was a significant association between increasing waist circumference (p = 0.009) and High FBS levels (p = 0.032) with the presence of DR. Conclusion Approximately two-thirds of the patients with T2DM aged >45 years and above have diabetic retinopathy. High FBS and waist circumference were associated with DR.
Copyright © 2022, Ranganathan et al.

Entities:  

Keywords:  diabetes; diabetic retinopathy; fasting blood sugar; india; waist circumference

Year:  2022        PMID: 36158357      PMCID: PMC9494576          DOI: 10.7759/cureus.28291

Source DB:  PubMed          Journal:  Cureus        ISSN: 2168-8184


Introduction

Diabetes mellitus (DM) is a metabolic condition that is caused by problems in insulin production, its action, or both. It is distinguished by chronic hyperglycemia and irregularities in carbohydrate, lipid, and protein metabolism [1]. Type 2 diabetes mellitus (T2DM) is the most prevalent form of diabetes, which accounts for 90% of all diabetics worldwide [1,2]. Individuals with T2DM are more likely to develop complications, such as cardiovascular disease (CVD), neuropathy, eye disease (retinopathy), and nephropathy. This retinopathy may lead to blindness [3,4]. DM has a long-term impact on retinal tiny blood vessels, culminating in the progression to retinopathy and visual impairment. Diabetic retinopathy (DR) is the leading cause of visual impairment in adults aged 20-65 years; one in three people with diabetes have some degree of DR and one in 10 develop a vision-threatening form of the illness. Globally, the number of persons with DR is expected to rise from 126.6 million in 2010 to 191.0 million by 2030, with the number of people with vision-threatening DR rising from 37.3 to 56.3 million if immediate action is not taken [5,6]. DR is asymptomatic until it has progressed to an advanced stage; however, it is mostly preventable with frequent ocular screenings and appropriate treatment before vision impairment. Gender, unregulated DM, chronic DM, the associated complication of nephropathy, and comorbidity with hypertension are risk factors for DR in diabetic patients [7-9]. However, screening for DR is not widely used due to a lack of accessibility and economic constraints, especially in resource-limited settings. Thus, a longitudinal marker that is associated with the development of DR is required. To date, few studies have assessed any association with DR. Therefore, this study was conducted to assess the association between DR, fasting blood sugar (FBS) levels, and waist circumference.

Materials and methods

Study design and sampling A cross-sectional study was conducted in a tertiary care hospital in Salem for a duration of one year (July 2021 to July 2022). Study participants were included using a convenient sampling technique. Sample Size Previous studies have shown that the prevalence of DR among diabetes is 5-7%. Thus, with a 7% prevalence and 5% absolute error, the minimum sample size needed for the current study with a 95 percent confidence interval is 120 (inclusive of a 10% non-response rate). The sample size was calculated by using the formula 3.86*p*q/d2, where, p is prevalence, q is a compliment of p and d is absolute precision (5%). Ethical Clearance This study obtained ethical approval from the Institutional Ethical Committee at Vinayaka Mission’s Kirupananda Variyar Medical College and Hospitals (VMKVMC&H), Salem (approval number VMKVMC&H/ICE/21/118). Eligibility criteria Inclusion criteria: After obtaining informed consent, all individuals who were recruited during the study period with the diagnosis of T2DM and were ≥45 years of age were included in the study. Exclusion criteria: Individuals with fasting blood glucose levels of <126 mg/dl; those diagnosed with terminally ill conditions; and those <3 years from their T2DM diagnosis were excluded from the study. Similarly, all patients who were diagnosed with impaired glucose tolerance, maturity-onset diabetes of the young (MODY), latent autoimmune diabetes in adults (LADA), and Type 1 DM were also excluded from the study. Data collection All study participants provided 12-hour overnight fasting blood samples, which were sent for laboratory analysis. The circumference line connecting the narrowest point between the inferior border of the lower rib, iliac crest, and umbilicus was used to measure the waist circumference. The normal waist circumference range for men and women is less than 90 and less than 80 centimeters respectively. Individuals presented with ≥1 retinal micro-aneurysm or retinal blot hemorrhages, with or without any additional abnormalities, while doing ophthalmoscopy, were diagnosed as DR. Data analysis The data obtained from the study were entered in Microsoft Excel. The results were analyzed using SPSS version 21 (IBM Corp., Armonk, NY). Continuous variables were expressed as mean and standard deviation. The association between FBS and waist circumference with DR was assessed by using an independent t-test. Data were considered statistically significant with a 95% confidence interval when p < 0.05.

Results

This study included 213 individuals. The mean age, duration of diabetes, height, and weight were 60.46 years, 10.02 years, 161.24 cm, and 61.6 kg, respectively (Table 1).
Table 1

Distribution of the study participants according to their age and duration of diabetes mellitus (n = 213)

 Age in yearsDuration of DiabetesHeight in CentimetersWeight in Kilogram
Mean60.4610.02161.2461.61
Median62.008.00162.0061.00
Mode62316253
Std. Deviation9.1897.3488.17412.345
Minimum40314233
Maximum844018897
Interquartile range53.5 - 66.0156 - 16754 - 684 - 15
The general characteristics of the study participants are described in Table 2. Approximately 55.9% of the study participants were males (n = 119). The prevalence of hypertension and being overweight was 13.6% and 24.9%, respectively. The prevalence of diabetic retinopathy among the study participants was 67.6%.
Table 2

General characteristics of the study participants (n = 213)

S. No General characteristics Frequency Percent
1 Gender Female 94 44.1
Male 119 55.9
Total 213 100.0
2 Diabetic retinopathy No 69 32.4
Yes 144 67.6
Total 213 100.0
3 Hypertension No 184 86.4
Yes 29 13.6
Total 213 100.0
4 High cholesterol No 183 85.9
Yes 30 14.1
Total 213 100.0
5 Body Mass Index category Underweight 16 7.5
Normal 144 67.6
Overweight 53 24.9
Total 213 100.0
The Body Mass Index (BMI), waist circumference, and waist-hip ratio were shown in Table 3. The mean BMI among the study participants was 23.652. Similarly, the mean waist circumference was 39.04 inches.
Table 3

Distribution of the study participants according to their BMI, Waist circumference, and Waist hip ratio (n = 213)

  Body Mass Index Waist circumference in Inch Waist hip ratio
Mean 23.6526 39.04 .9236
Median 22.8624 38.00 .9184
Mode 23.62 34 .83
Std. Deviation 4.34557 5.452 .18682
Minimum 15.70 26 .10
Maximum 39.86 52 2.69
Percentiles 25 21.3599 35.00 .8799
50 22.8624 38.00 .9184
75 24.9880 43.50 .9444
Similarly, the mean fasting blood sugar (FBS) value, and systolic and diastolic blood pressure were 198.63 mg/dl, 132.70 mm Hg, and 76.81 mm Hg respectively (Table 4).
Table 4

Distribution of the study participants according to their FBS and blood pressure (n = 213)

FBS: Fasting blood sugar

 Fasting Blood Sugar in mg/dlSystolic Blood PressureDiastolic Blood Pressure
Mean198.36132.7076.81
Median204.00130.0080.00
Mode22913070
Std. Deviation49.27621.92110.778
Minimum1267050
Maximum323190120
Percentiles25151.00120.0070.00
50204.00130.0080.00
75229.00145.0080.00

Distribution of the study participants according to their FBS and blood pressure (n = 213)

FBS: Fasting blood sugar The mean FBS value for participants with and without DR was 203.36 and 187.93, respectively (Table 5), which was a significant difference (p = 0.032). The mean waist circumference for participants with and without DR was 39.72 and 37.64, respectively, which was also a significant difference (p = 0.009).
Table 5

Association between FBS and waist circumference and diabetic retinopathy (n = 213)

Risk Factors Diabetic retinopathy N Mean Standard Deviation Mean difference P-Value
Fasting Blood Sugar in mg/dl No 69 187.93 50.061 - 15.434 0.032
Yes 144 203.36 48.274
Waist circumference in Inch No 69 37.64 5.785 - 2.078 0.009
Yes 144 39.72 5.172

Discussion

This study found that the prevalence of DR among individuals with T2DM aged ≥45 years was 68%. A similarly high prevalence rate of 51% was found by Kaushik et al. in a hospital-based study conducted in a tertiary care center in Kashmir, India, in 2021 (N = 625) [10]. A hospital-based multicentric study performed across India by Rajalakshmi et al. in 2016 (N = 11,182) found a prevalence of 33% DR in the study population with a mean age of 58 years [11]. This difference may be due to sample size differences and a multi-centric approach. A population-based study (N = 63,000, age ≥50 years) involving 31 districts showed a prevalence of only 16.9% [12]. This study used data from a national survey from 2015-2019. This big difference could be due to differences in the study setting and sample size. Further research is required to confirm the true prevalence. Our study showed a significant association between increased waist circumference and the presence of DR. Similar results have been reported in a Chinese population (N = 511) study [13]. That study assessed the association between central obesity (defined by waist circumference) and DR. Results indicated that individuals with central obesity are 1.07X more likely to have DR (95% confidence interval, 1.03-1.10). Further, Man et al. have shown that obesity, as defined by BMI, is protective against developing DR, whereas central obesity, as defined by waist circumference, is significantly associated with DR [14]. This indicates the importance of waist circumference among diabetic patients when considering the risk of developing DR. In contrast to our study, Wat et al. have reported no significant association between obesity and DR [15]. A review article by Mbata et al. has discussed a significant association between metabolic syndrome and the development of DR; however, there are conflicting data regarding the individual factors of metabolic syndrome on the development of DR, especially in non-diabetic individuals [16]. Taken together, these data highlight that central obesity/obesity among individuals with T2DM diabetics does not have a confirmed association with the presence of DR. Our study showed a significant association between increased waist circumference and DR; however, further evaluation is required. Moreover, we found a significant association between high FBS and the presence of DR. Similarly, a study by Yin et al. has found a significant association between FBS and the prevalence of DR among individuals with diabetes [17]. Another cross-sectional study undertaken in China by Cui et al. found a similar association among 17,985 participants [18]. Further, Kumar et al. have shown that FBS and post-prandial blood sugar (PPBS) levels along with triglyceride levels are significantly associated with the prevalence of DR [19]. An indirect association was shown by Mujeeb et al. with 150 diabetes patients; FBS is associated with the urinary protein-creatine ratio, which in turn is associated with the prevalence of DR [20]. Therefore, our data add to the strength of the association between FBS and the presence of DR. Strengths and limitations of the study This study follows a convenient sampling technique; however, a fair number of study participants were included in the study. All the data and measurements were collected by a single investigator, which eliminated any inter-observer bias. This study was performed in a tertiary care setting alone, which may cause Berksonian Bias. A multicentric or a community-based study would provide more reliable results when assessing the prevalence of DR.

Conclusions

Approximately two-thirds of individuals with diabetes who were ≥45 years of age had DR in our study sample. High FBS levels and increased waist circumference were significantly associated with the presence of DR. Therefore, FBS and waist circumference may be useful tools to indicate further screening for DR, especially in low-resource settings.
  19 in total

1.  Definition, classification and diagnosis of diabetes, prediabetes and metabolic syndrome.

Authors:  Ronald Goldenberg; Zubin Punthakee
Journal:  Can J Diabetes       Date:  2013-03-26       Impact factor: 4.190

Review 2.  Obesity, metabolic syndrome and diabetic retinopathy: Beyond hyperglycemia.

Authors:  Osinakachukwu Mbata; Nada Fawzy Abo El-Magd; Azza Bahram El-Remessy
Journal:  World J Diabetes       Date:  2017-07-15

3.  Prevalence and factors associated with diabetic retinopathy among diabetic patients at Arbaminch General Hospital, Ethiopia: Cross sectional study.

Authors:  Yilma Chisha; Wondwossen Terefe; Huruy Assefa; Serawit Lakew
Journal:  PLoS One       Date:  2017-03-02       Impact factor: 3.240

4.  Association of serum magnesium with type 2 diabetes mellitus and diabetic retinopathy.

Authors:  Pratyush Kumar; Seema Bhargava; Pankaj Kumar Agarwal; Ambuj Garg; Amit Khosla
Journal:  J Family Med Prim Care       Date:  2019-05

5.  Spectrum of eye disorders in diabetes (SPEED) in India. Report # 2. Diabetic retinopathy and risk factors for sight threatening diabetic retinopathy in people with type 2 diabetes in India.

Authors:  Ramachandran Rajalakshmi; Umesh C Behera; Harsha Bhattacharjee; Taraprasad Das; Clare Gilbert; G V S Murthy; Hira B Pant; Rajan Shukla
Journal:  Indian J Ophthalmol       Date:  2020-02       Impact factor: 1.848

6.  Profile of sight-threatening diabetic retinopathy and its awareness among patients with diabetes mellitus attending a tertiary care center in Kashmir, India.

Authors:  Madhurima Kaushik; Shah Nawaz; Tariq Syed Qureshi
Journal:  Indian J Ophthalmol       Date:  2021-11       Impact factor: 1.848

7.  Prevalence of diabetic retinopahty in India: Results from the National Survey 2015-19.

Authors:  Praveen Vashist; Suraj S Senjam; Vivek Gupta; Souvik Manna; Noopur Gupta; B R Shamanna; Amit Bhardwaj; Atul Kumar; Promila Gupta
Journal:  Indian J Ophthalmol       Date:  2021-11       Impact factor: 1.848

Review 8.  The worldwide epidemic of diabetic retinopathy.

Authors:  Yingfeng Zheng; Mingguang He; Nathan Congdon
Journal:  Indian J Ophthalmol       Date:  2012 Sep-Oct       Impact factor: 1.848

9.  Prevalence and associated factors of diabetic retinopathy in Beijing, China: a cross-sectional study.

Authors:  Jing Cui; Ji-Ping Ren; Dong-Ning Chen; Zhong Xin; Ming-Xia Yuan; Jie Xu; Qi-Sheng You; Jin-Kui Yang
Journal:  BMJ Open       Date:  2017-08-30       Impact factor: 2.692

10.  Is central obesity associated with diabetic retinopathy in Chinese individuals? An exploratory study.

Authors:  Jian-Bo Zhou; Jing Yuan; Xing-Yao Tang; Wei Zhao; Fu-Qiang Luo; Lu Bai; Bei Li; Jia Cong; Lu Qi; Jin-Kui Yang
Journal:  J Int Med Res       Date:  2019-09-23       Impact factor: 1.671

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