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Research Article

Prevalence, Characteristics and Risk Factors Analysis of Prediabetes: A Cross-Sectional Study

[version 1; peer review: 2 not approved]
PUBLISHED 29 Jul 2024
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Abstract

Background

Prediabetes, a reversible condition before the onset of diabetes, is a significant concern in healthcare globally. The global prediabetes epidemic has emerged and has considerably impacted health expenditures. Various risk factors play important roles in the progression of prediabetes to diabetes. Intensive lifestyle and pharmacological interventions can significantly reduce the risk of diabetes progression.

Objective

This study aimed to determine the prevalence, characteristics, and risk factors of prediabetes state of Medan in August 2023.

Methods

The sample consisted of 89 participants. This was an analytical cross-sectional study in the community that met the inclusion and exclusion criteria. The determination of prediabetes is based on the results of blood tests, namely, the examination of fasting blood sugar levels (FBGL), 2-hour postprandial oral glucose tolerance test (OGTT), and hemoglobin A1c (HbA1C). Other examinations included lipid profiling (total cholesterol, HDL-C, LDL-C, and triglycerides). Data processing was performed using SPSS via univariate and bivariate analyses (chi-square test).

Results

Of the 89 participants, the prevalence of prediabetes based on HbA1c, FBGL and 2-hours OGTT levels was 28.1%, 50.6%, and 28.1%, respectively. 82% of the participants were female, and 53.9% were overweight or obese based on body mass index (BMI). The risk factors related to the prevalence of prediabetes were HbA1c level, impaired FBGL, and impaired 2-hours OGTT. Other risk factors such as age, sex, daily exercise, diet, BMI, waist-hip ratio, acanthosis nigricans, lipid profile, and blood pressure did not correlate significantly with the risk factors (p>0.05).

Conclusion

This study found that the prevalence of prediabetes was 67.4% in Medan, 82% of the participants were female, and more than 50% of participants were overweight or obese. HbA1c, FBGL, and 2-hour postprandial OGTT were the most important risk factors for prediabetes.

Keywords

macrovascular complication, HbA1c, diabetes type 2, Prediabetes, Risk Factors

Introduction

Diabetes is a group of metabolic diseases and a serious, long-term (chronic) condition which characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both.13 Based on the 10th edition of the International Diabetic Federation (IDF) Atlas, the prevalence of diabetes is estimated to be 537 million adults aged 20–79 years worldwide (10.5%). This includes both type 1 and type 2 diabetes as well as diagnosed and undiagnosed diabetes. The adult population with diabetes aged between 20-79 years is estimated to be 19,465,100 in Indonesia. Instead, the prevalence of diabetes among the ages–20-79 years is 10.6% (of the total adult population aged 20-79 years is 179,720,500). In other words, one in nine people in Indonesia had diabetes.2 T2DM is one of the most important causes of morbidity and mortality worldwide.4

Prediabetes is a condition that results in high BGL and often leads to T2DM.5 People with prediabetes have high BGL (are below the amount needed to be diagnosed with diabetes, but they are at a higher risk of getting diabetes.6 According to the World Health Organization (WHO), prediabetes is an intermediate level of high blood sugar. They use two specific tests to define it: impaired FBGL, which means BGL of 6.1 to 6.9 mmol/L (110–125 mg/dL) before a meal, or impaired OGTT, which mean OGTT of 7.8 to 11.0 mmol/L (140–199 mg/dL) two hours after eating 75 g of oral glucose.7

According to the American Diabetes Association (ADA), the criterion for identifying impaired FBGL between 5.6 and 6.9 mmol/L (100-125 mg/dL), impaired OGTT between 7.8 and 11.0 mmol/L (140-199 mg/dL), and HbA1c levels between 5.7% and 6.4% (39-47 mmol/mol).8,9 Both definitions rely on FBGL measurements, 2-hour plasma glucose concentrations during an OGTT, and HbA1c concentrations.10 In Indonesia, the diagnostic criteria for prediabetes align with those established by the ADA.11 The significance of Impaired FBGL and impaired 2-hour postprandial OGTT is threefold: they signal an elevated chance of developing T2DM in the future, indicative of an existing heightened risk of cardiovascular disease (CVD), and identifying therapies that can prevent the onset of T2DM.2

Individuals with Impaired FBGL and impaired OGTT are at a high risk of developing T2DM, with up to 50% within five years.8,9 Untreated T2DM for a prolonged time can lead to complications such as retinopathy, neuropathy, CVD, or stroke.1214 These chronic implications contribute to diabetes distress and health expenditures.15,16 Diabetes distress is a hidden emotional burden in DM.17 Healthcare expenditure for people with diabetes is expected to reach 1,054 billion USD by 2045.18 The cost of managing individuals with T2DM and complications is two times higher than that for individuals without complications.19,20

Risk factors for prediabetes include BMI, waist circumference, ethnicity, family history, and sex.2,9,21 Other risk factors include hypertension, low levels of HDL cholesterol, smoking, and low levels of education and income.22 According to the RISKESDAS (National Basic Health Research) Indonesia, the increase in diabetes data is in line with the rise in obesity rates, a risk factor for diabetes, from 14.8% to 21.8% in 2013-2018. In addition, it is also in line with the increase in BMI from 11.5% to 13.6% and central obesity from 26.6% to 31%.23,24 Intensive lifestyle and pharmacological intervention can significantly reduce the risk of progression to diabetes in patients with impaired FBGL or Iimpaired OGTT.25,26

This study aimed to investigate the prevalence, characteristics, and risk factors for prediabetes in Medan, Indonesia.

Methods

Study design and selection criteria

A cross-sectional study of a community that fulfilled the eligibility criteria was conducted in Medan, Indonesia. The participants were people who were at least 18 years old. Participants who had been diagnosed with diabetes or were pregnant were excluded criteria. A day before the study, all participants were reminded to fast for 8 hours and were only allowed to drink plain water before we assessed their FBGL. The minimum number of participants was determined using the Slovin formula. This formula allows calculation of the minimum sample size based on an acceptable margin of error.27

Data collection

Data were collected in August 2023 in Medan, Indonesia. Participation in this study is voluntary; participants are not obligated to participate. Earlier, the researcher provided an explanation regarding the ongoing research and their active participation in it. Subsequently, patients who gave their consent would sign the informed consent form. Participants then provided their background information, physical activity, consumption of vegetables or fruits, and history of high blood glucose (during pregnancy or medical checkups). Physical activity is defined as physical activity during work or leisure time (including daily activities) for at least 30 min. We also obtained information about a nigricans to identify additional risk factors for prediabetes. The study instrument was filled in by the participants themselves, followed by the measurement of their height, weight, waist circumference, hip circumference, systolic and diastolic blood pressure (SBP and DBP), lipid profile, FBGL, HbA1c, and 2-hour postprandial OGTT levels.

Ethical statement

The research design was approved by the Ethics Committee of the Faculty of Medicine, Universitas Sumatera Utara. The approval number is 896/KEPK/USU/2023 (Approval date: 21 August 2023). Patient participation is voluntary; patients have no compulsion to participate in this research. Previously, the researcher explained the research protocol that would be carried out. If the patient agreed, they signed informed consent.

Data measurement

Body Height, body weight, waist circumference, and hip circumference were measured by trained research assistants. While weighing, we asked participants to take off their footwear and only wear loose clothing. Waist circumference and hip circumference were measured using a non-stretchable tape. Patients were defined as centrally obese if they had a waist circumference of >90 cm in men and >80 cm in women. The blood pressure was measured using a digital blood pressure monitor (Omron™). FBGL, HbA1c, and 2-hour postprandial OGTT levels were measured using venous blood. The process of collecting blood was conducted in two distinct phases. The initial phase was conducted following an 8-hour fasting period by the patient, the examination included measuring the patient’s FBGL, HbA1C, and lipid profile. Subsequently, the patient was administered 75 grams of glucose (sugar dissolved in water) for the OGTT assessment, and the 2 hours post-prandial was monitored. The lipid profile was checked using the enzymatic colorimetric method (Thermo Scientific™ Indiko™ Plus Clinical Chemistry Analyzer).28 The hexokinase method (NIPRO Premier S Blood Glucose Monitoring System GM01IAA) was used to find the FBGL and 2-hour post-meal OGTT levels.29 High-performance liquid chromatography (HPLC) was used to determine HbA1c levels (BIORAD D-10 Hemoglobin Testing System).30

Statistical analysis

We conducted univariate analysis to determine the prevalence and demographic characteristics. Bivariate analysis was used to analyze the risk factors for prediabetes in Medan, Indonesia, using the Chi Square Test (p<0.05). Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS Inc.).

Results

Characteristics of patients

Table 1 shows that the majority of the 89 participants were housewives (69.7%) and women (82%). 40.4 Of the participants, 40.4% had a high school education, 31.5% were age range–45-54 years old, 56.2% were never engaged in physical activity, and 51.7% consumed vegetables/fruits.

Table 1. Frequency distribution based on demographic characteristics.

CharacteristicsFrequency (n = 89)Percentage (%)
Gender
 Men1618
 Women7382
Age (years)
 <452629.2
 45-542831.5
 55-642325.8
 >641213.5
Education
 Elementary School2629.2
 Junior High School1314.6
 Senior High School3640.4
 Diploma22.2
 Bachelor1112.4
 Doctoral degree11.1
Employment
 Housewife6269.7
 Student11.1
 Entrepreneur1618
 Civil servants66.7
 Private employee44.5
Physical activity
 Never3943.8
 More than 30 min5056.2
Consuming vegetables/fruits
 Everyday4651.7
 Not everyday4348.3

A total of 25 people had prediabetes based on HbA1c measurement, 45 had prediabetes based on FBGL measurement, and 25 had prediabetes based on 2-hour postprandial OGTT levels measurement. The prevalence of prediabetes based on HbA1c, FBG, and 2-hour postprandial OGTT was 28.1%, 50.6%, and 28.1%, respectively (Table 2).

Table 2. Prevalence of prediabetes based on HbA1c, FBGL and 2-h postprandial OGTT examination.

MeasurementFrequency (n= 89)Percentage (%)
HbA1c Levels
 Normal5056.2
 Prediabetes2528.1
 Diabetes1415.7
Fasting Blood Glucose Levels
 Normal3033.7
 Prediabetes4550.6
 Diabetes1415.7
2 Hours Postprandial OGTT Levels
 Normal4955.1
 Prediabetes2528.1
 Diabetes1516.9

Table 3 shows the waist-hip circumference ratio: 66 participants (74.2%) were obese. Based on the blood pressure examination, the median systolic and diastolic blood pressures were 142 and 86 mmHg, respectively. Based on laboratory results, the median serum total cholesterol, HDL, triglycerides levels were 206 mg/dL, 53 mg/dL, 125 mg/dL respectively.

Table 3. The result of physical examination and laboratory.

CharacteristicsMeanMedian95% Confidence Interval (CI)Minimum-Maximum
BMI26.61 kg/m226.14 kg/m225.53-27.6813.23-41.87 (kg/m2)
Waist-hip ratio1.742.001.65-1.831-2
Systolic Blood Pressure141.03 mmHg142 mmHg136.42-145.65100-204 (mmHg)
Diastolic Blood Pressure87.12 mmHg86 mmHg84.60-89.6466-131 (mmHg)
Total Cholesterol209.66 mg/dL206 mg/dL198.76-220.57127-471 (mg/dL)
HDL54.48 mg/dL53 mg/dL51.70-57.2727-89 (mg/dL)
LDL124.87 mg/dL122 mg/dL116.53-133.2030-238 (mg/dL)
Triglycerides142.87 mg/dL126 mg/dL123.87-161.8651-738 (mg/dL)
Fasting blood glucose116.64 mg/dL106 mg/dL108.24-125.0477-311 (mg/dL)
2-hours postprandial OGTT157.70 mg/dL136 mg/dL143.44-172.0375-521 (mg/dL)
HbA1c6.08%5.60%5.72-6.454.5-13%

As shown in Table 4, the risk factors for prediabetes were significantly correlated if the p-value was <0.05. According to the chi-square analysis, there was no significant relationship between risk factors, such as age, sex, daily exercise, consumption of vegetables/fruits, BMI, HDL, LDL, triglyceride, total cholesterol, acanthosis nigricans, and systolic and diastolic blood pressure in prediabetes patients. Meanwhile, risk factors, including HbA1c, FBGL, and 2-hours postprandial OGTT, have a significant relationship with prediabetes.

Table 4. Analysis risk factors of prediabetes.

Risk factorsPrediabetesNon-prediabetesp-value
Frequency (n)Percentage (%)Frequency (n)Percentage (%)
Age (years)0.401
 <451719.1910.1
 45-5416181213.5
 55-641820.255.6
 >64910.133.4
Gender0.313
 Male1314.633.4
 Female4752.82629.2
Daily Exercise0.925
 Never2730.31213.5
 More than 30 min3337.11719.1
Consuming vegetables/fruits0.494
 Everyday2932.61719.1
 Not everyday3134.81213.5
Body Mass Index0.865
 Normoweight1213.577.9
 Obesity4853.92224.7
High Density Lipoprotein (mg/dL)1.00
 <604044.91921.3
 ≥602022.51011.2
Low Density Lipoprotein (mg/dL)0.603
 <1001415.7910.1
 ≥1004651.72022.5
Trygliceride (mg/dL)0.198
 <1504146.11516.9
 ≥1501921.31415.7
Total Cholesterol (mg/dL)0.508
 <2002325.81415.7
 ≥2003741.61516.9
2-h Postprandial OGTT (mg/dL)<0.05*
 <1403438.21516.9
 140-199242711.1
 ≥20022.21314.6
HbA1c (%)<0.05*
 <5.73539.31516.9
 5.7-6.42528.100
 ≥6.5001415.7
Fasting Blood Glucose (mg/dL)<0.05*
 <1001516.91516.90.526
 100-1254449.411.1
 ≥12611.11314.6
Systolic Blood Pressure (mmHg)0.202
 <1402528.11719.10.137
 ≥1403539.31213.5
Diastolic Blood Pressure (mmHg)0.775
 <903842.72022.50.245
 ≥902224.7910.1
Achantosis Nigricans0.548
 Yes11.111.1
 No5966.32831.5
Waist-hip Ratio0.603
 Normal1415.7910.1
 Obesity4651.72022.5

* Statistical significance (p<0.05).

Discussion

Our study demonstrated that the prevalence of individuals with prediabetes in Medan, Indonesia, using HbA1c, FBGL, and 2-hours postprandial OGTT were 28.1%, 50.6%, and 28.1%, respectively. The prevalence of prediabetes based on FBGL examinations in 33 provinces in Indonesia was 10%.31 In this study, the prevalence of prediabetes using FBGL was one-fifth of that in the previous study. Another study found that the prevalence of prediabetes in Pontianak with an FBGL > 100 mg/dL was 76.5%. A significant increase in the prevalence of prediabetes has also been reported in the US, Europe, North America, the Caribbean, Africa, West Iran, and Malaysia.32,33 The global prevalence of prediabetes using FBGL and 2-hours postprandial OGTT is estimated to increase to 6.5% and 10%, respectively, in 2045.8

In this study, we found that most patients with prediabetes were 55-64 years old. Similar to the study by Andriani et al., the majority of prediabetic patients were > 50 years old. However, in this study, age was not significantly correlated with the incidence of prediabetes. A previous study found a significant relationship between age and incidence of prediabetes (p=0.029).22 Numerous additional factors that may impact the etiology of prediabetes are also associated with advanced age. Peripheral insulin resistance is increasing in tandem with these processes. with a poor diet, little exercise, or obesity. Hyperglycemia results if this process occurs in people who are at risk of developing prediabetes. The degree of environmental exposure and lifestyle choices have a significant impact on the rate and timing of development.22

The frequency of physical inactivity in the subjects diagnosed with prediabetes in this study was 37.1% (p= 0.925). This contradicts the claim that a sedentary lifestyle influences the development of prediabetes and diabetes. Exercise helps to avoid obesity and increases insulin sensitivity. Compared to people who exercise, those who do not exercise may be more susceptible to developing prediabetes and diabetes.34 Our study showed that there was no correlation between physical activity, diet, hyperlipidemia, and prediabetes. This study is in accordance with previous studies that stated that physical activity, diet, and hypercholesterolemia had no relationship with the incidence of prediabetes. Although physical activity is known to be protective against the onset of type 2 diabetes,35 Redondo et al.36 did not find a correlation between prediabetes and noncompliance with the WHO physical activity guidelines. Similar results have been obtained in other investigations.

In this study, we found that most patients with prediabetes were female, overweight, or obese. This study is consistent with research conducted in Pontianak, showing that female and overweight or obesity are more prevalent among people with prediabetes.22 However, in this study, we found that sex and BMI were not significantly correlated with the incidence of prediabetes.

Another study showed that sex and BMI were associated with prediabetes. Premenopausal women with prediabetes are prone to cardiometabolic risk factors and a threefold risk of obesity and central obesity.37 Our study showed that 82% of the respondents were women. Women of reproductive age are less susceptible to cardiovascular disease because of the protective effects of estrogen. Estrogen commonly reduces triglyceride and LDL-C circulating levels, while increasing HDL-C levels. However, some studies have mentioned the development of cardiovascular disease in women with lower blood glucose levels than in men.3840 The mean BMI in this study was 26.61 (95% CI 25.53-27.68). BMI is a risk factor for prediabetes. BMI is a simple anthropometric measure commonly used to measure general adiposity.37 Asian populations have more visceral fat than Caucasian populations do. This results in metabolic disorders, lipotoxicity, and insulin resistance. In addition, limited insulin secretory capacity and genetic predisposition play important roles in the development of insulin resistance. Several studies have reported that there is no relationship between BMI and the obesity paradox, and BMI acts as a simple indicator for evaluating the risk of blood glucose and lipid metabolism.41 Maintaining a normal weight BMI is essential in the education of patients with prediabetes and is a concern for physicians.42

In this study, of 16 risk factors, only 3 risk factors have significant correlation with prediabetes in Medan (p<0.05), namely HbA1c, IFG, and IGT. The American Diabetes Association (ADA) defines impaired fasting glucose (IFG) as having a fasting plasma glucose (FPG) level of 100–125 mg/dL, impaired glucose tolerance (IGT) as having a 2-hour postprandial glucose of 140–199 mg/dL, or elevated HbA1c (5.7%–6.4%) as having “prediabetes,” or intermediate hyperglycemia, and advises this population to make preventative efforts. Similar to the study by Barry et al., the majority of prediabetic participants in their sample showed elevated HbA1c (51%), IFG (67%), and IGT (32%) was significantly lower.43 This is a new finding that has never been published in this manner: women are significantly more likely than males to have elevated HbA1c levels.

Women are more likely than men to have increased HbA1c readings, which is a novel finding not previously documented in this manner. There was a substantial difference in the joint distribution of IGT, IFG, and elevated HbA1c values between men and women. Statistics suggest that the specific definition of prediabetes used can significantly impact the percentage of women and men who are classified as having prediabetes and are eligible for targeted lifestyle treatments to prevent diabetes. However, the exact reason for this observation is still unclear.40

Preventing T2DM provides significant public health benefits, including lower rates of complications.44 Implementing lifestyle counselling in clinical practice is feasible and cost-effective.45 Program-intensive lifestyle interventions from the DPP were to achieve and maintain a minimum weight loss of 7% and a physical activity of 150 min per week identical in intensity to brisk walking. The goal of physical activity was to approximate at least 700 kcal/week of physical activity.46 The 12-week intervention consisted of four nutrition visits and instructions on a high-carbohydrate diet (60% to 70% daily calories), high-fiber diet, and low-fat diet (<7% calories from saturated fat). The results showed 5% weight loss.44 In a study of participants at a high risk of diabetes, dietary fiber intake lowered postprandial blood glucose and insulin resistance. The recommended dietary fibre intake recommendation is 3.0 g or 1,000 kcal of total energy per day to prevent T2DM.16 Holistic and integrated coordination is needed to assess the disease, including early detection in high-risk factor populations, targeted treatment, and intensive lifestyle modification.

Conclusion

This study found that The prevalence of prediabetes in the Medan group was 67.4%. 82% of the participants were female, and more than half were overweight or obese based on body mass index. Risk factors such as HbA1c, IFG, and IGT were significantly correlated with the incidence of prediabetes in Medan. Early detection is necessary to assess high-risk factors, targeted treatment, and intensive lifestyle modifications.

Ethical statement

The research design was approved by the Ethics Committee of the Faculty of Medicine, Universitas Sumatera Utara. The approval number is 896/KEPK/USU/2023 (Approval date: 21 August 2023). Patient participation is voluntary; patients are not compelled to participate in this research. Before being included in the research, patients are given an informed consent sheet containing information about research procedures, blood examinations, the discomfort they will experience when taking blood, and other matters related to the research. If the patient understands and is willing to participate, they must sign the informed consent sheet.

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Amelia R, Harahap J, Wijaya H et al. Prevalence, Characteristics and Risk Factors Analysis of Prediabetes: A Cross-Sectional Study [version 1; peer review: 2 not approved]. F1000Research 2024, 13:843 (https://doi.org/10.12688/f1000research.150600.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 1
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PUBLISHED 29 Jul 2024
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Reviewer Report 18 Sep 2024
Rajendra Pradeepa, Madras Diabetes Research Foundation, Tamil Nadu, India 
Not Approved
VIEWS 9
Thank you for asking me to review the article entitled “Prevalence, Characteristics and Risk Factors Analysis of Prediabetes: A Cross-Sectional Study” conducted in Medan, Indonesia. The study aimed to determine the prevalence, characteristics, and risk factors of prediabetes state of ... Continue reading
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Pradeepa R. Reviewer Report For: Prevalence, Characteristics and Risk Factors Analysis of Prediabetes: A Cross-Sectional Study [version 1; peer review: 2 not approved]. F1000Research 2024, 13:843 (https://doi.org/10.5256/f1000research.165188.r317377)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 30 Aug 2024
Hanaa Reyad Abdallah, National Research Centre, Cairo, Egypt 
Not Approved
VIEWS 12
This manuscript gives information about the prevalence of pre-diabetes in  Medan state in Indonesia which was diagnosed by three methods; HbA1c, OGTT and FBG. the authors also investigated factors associated with pre-diabetes occurrence in those people. Here are my comments ... Continue reading
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Abdallah HR. Reviewer Report For: Prevalence, Characteristics and Risk Factors Analysis of Prediabetes: A Cross-Sectional Study [version 1; peer review: 2 not approved]. F1000Research 2024, 13:843 (https://doi.org/10.5256/f1000research.165188.r313859)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.

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Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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