Abstract
Purpose
The prevalence of diabetes is increasing worldwide. Studies have shown that poor blood sugar control is associated with the complications of diabetes, we aimed to determine the prevalence of uncontrolled diabetes mellitus (UDM) and its related factors.
Methods
This multicenter cross-sectional study was conducted in 2021 on type 2 diabetic patients in three cities; Rasht (in Gillan province), Borujerd (in Lorestan province), and Khodabandeh (in Zanjan province). A predesigned checklist was used to extract the basic characteristics of participants, their hemoglobin A1C, and other required data from their medical records. The prevalence of uncontrolled diabetes was reported with a 95% Confidence Interval.
Results
In this study, the medical records of 460 patients with type 2 diabetes were included. The mean and standard deviation (SD) of the age of participants was 59.17 (11.59), and 73.2% (337) of participants were female. The prevalence of UDM in Rasht, Borujerd, and Khodabandeh was 58.27%, 69.38%, and 45.65% respectively. The prevalence of UDM in obese patients was 64.78% (57.03, 71.82). Based on the results of the adjusted model, an increase in diastolic blood pressure was significantly associated with UDM, meaning each unit increase in diastolic blood pressure was associated with a 3% increase in UDM (95% CI: 1.01, 1.06), adjusted for age, gender and education.
Conclusion
According to these results, the prevalence of UDM among patients with diabetes is high. Diastolic blood pressure and low level of education were associated with UDM in diabetic patients.
Keywords: Prevalence, Uncontrolled diabetes mellitus, Blood glucose
Introduction
Diabetes is a chronic disease characterized by insulin resistance or deficiency that results in elevated glycosylated hemoglobin A1C (HbA1C) levels [1]. Type 2 diabetes is more common in people over 45, but has also increased in children, adolescents, and young adults [2]. Diabetes is the seventh leading cause of death and the most critical cause of debilitating complications such as heart attack, stroke, kidney failure, blindness, and lower limb amputation [3].
The prevalence of diabetes is increasing worldwide. According to the International Diabetes Federation (IDF) in 2019, 463 million people had diabetes [4], and this number is projected to reach 578 million in 2030 and 700 million in 2045 [5, 6]. In 2019 alone, approximately 4.2 million people died due to diabetes worldwide. In the Eastern Mediterranean countries (EMR), Iran is projected to have a high prevalence of diabetes by 2030 [7]. The prevalence of diabetes in recent years has been mainly due to the growing obesity epidemic [8]. Based on the conducted studies prevalence of uncontrolled diabetes mellitus (UDM) is ranged from 38.9 to 76.9% among patients with type 2 diabetes [9–11]. Some factors such as older age, male gender, smoking, longer disease duration, hypertension, illiteracy, being employed, and obesity are associated with UNM [9].
Studies have shown that UNM is associated with major complications in patients and reasonable control of diabetes can prevent these complications [12, 13]. Also, increasing the patient’s knowledge about the disease and its complications has significant benefits in terms of patient adaptation to treatment and reducing disease-related complications [14].
Based on our best knowledge there is not sufficient evidence regarding the prevalence of UDM in Iran. Therefore, we aimed to determine the prevalence of UDM and its related factors in three cities in Iran including Rasht, Borujerd, and Khodabandeh.
Method
The proposal of this study was approved by the ethics committee of Hamadan university of medical sciences (IR.UMSHA.REC.1399.387.) This multicenter cross-sectional study was conducted in 2021 on type 2 diabetic patients in three cities; Rasht (Gillan province, north of Iran) Borujerd (Lorestan province, West of Iran), and Khodabandeh (Zanjan province, Northwestern of Iran).
The eligibility criteria in this study were patients with type 2 diabetes mellitus and written HbA1C test in their electronic health records. Pregnant women and diabetic patients with serious complications of the disease were excluded from the study.
We designed a checklist that includes demographic characteristics like age, sex, marital status, height, weight and education, diagnosis date of disease, and related factors such as physical activity and smoking use status. The used definitions of physical activity and smoking in the medical recoreds of patients was as follow. Physical activity was defined as 30 min of moderate physical activity for at least five times a week or 25 min of vigorous activity at least three times a week. A smoker was a person who consumes one or more types of tobacco products daily or non-daily in the last month. We also extracted their HbA1C from their medical records in comprehensive urban and rural service centers. The sample size was calculated at a 95% confidence level, and the value of P and precision were considered as 0.50 and 0.05 respectively, we reached 384 participants. However, we increased the calculated sample size by 20%, and finally our sample size reached 460. Based on the number of patients with electronic records in mentioned cities the calculated sample size was assigned to each city. Therefore, in Rasht with 15,078, Borujerd with 5081, and Khodabandeh with 665 patients with active records, 254, 160, and 46 samples were assigned respectively.
Hemoglobin A1c levels are measured to determine the blood sugar level of people with type 2 diabetes. The UDM was defined based on the HbA1c levels. The patients with HbA1c ≤ 7 are classified as good control blood sugar and patients with HbA1c > 7 are classified as UDM [15].
Statistical analysis
Quantitative variables were reported as mean and standard deviation and categorical variables were reported as frequency and percentage. The prevalence of UDM in patients was calculated. The t-test and one-way analysis of variance were used to compare the HbA1C between the categorical variables. The association of the UDM and independent variables was assessed by logistic regression. Stata version 16 (StataCorp, TX, US) was used for data analysis. The results were reported at a 95% confidence level.
Results
In this study, the health records of 460 patients with type 2 diabetes were included. The proportion of females was 73.26%. The mean age (standard deviation (SD)) of patients was 59.17 (11.59). The mean (SD) of HbA1C was 7.81 (2.03). Other characteristics of patients are shown in Table 1. The total prevalence of UDM was 60.78 (95% CI: 56.32, 65.24). The prevalence of UDM in Rasht, Borujerd, and Khodabandeh was 58.27%, 69.38%, and 45.65% respectively. The prevalence of UDM in obese patients and patients with no physical activity was 64.78% (57.03, 71.82), and 63.46% (57.42, 69.11) respectively (Table 1).
Table 1.
characteristics of patients with type 2 diabetes and prevalence of UDM in patients based on baseline characteristics
| Categorical variables | Number (percent) | Prevalence (95% CI) |
|---|---|---|
| Gender | ||
| Female | 337 (73.26) | 60.83 (55.50, 65.92) |
| Male | 123 (26.74) | 60.98 (52.07, 69.20) |
| Age group (years) | ||
| 24–44 | 49 (10.65) | 46.94 (33.51, 60.82) |
| 45–69 | 324 (70.43) | 63.89 (58.50, 68.95) |
| 70–91 | 87 (18.91) | 57.47 (46.88, 67.42) |
| Education | ||
| Illiterate | 152 (33.12) | 61.84 (53.86, 69.23) |
| Elementary | 150 (32.68) | 68.00 (60.10, 74.98) |
| Middle school | 86 (18.74) | 53.49 (42.92, 63.75) |
| High school diploma/ university | 71 (15.47) | 52.11 (40.56, 63.45) |
| City | ||
| Rasht | 254 (55.22) | 58.27 (52.09, 64.19) |
| Borujerd | 160 (34.78) | 69.38 (61.79, 76.04) |
| Khodabandeh | 46 (10.00) | 45.65 (31.95, 60.04) |
| Marital status | ||
| Single | 80 (17.39) | 61.25 (50.17, 71.28) |
| Married | 380 (82.61) | 60.79 (55.77, 65.59) |
| Body Mass Index | ||
| < 25 | 85 (18.48) | 56.47 (45.77, 66.60) |
| 25–30 | 216 (46.96) | 59.72 (53.03, 66.07) |
| > 30 | 159 (34.57) | 64.78 (57.03, 71.82) |
| Underlying diseases | ||
| No | 158 (34.35) | 58.23 (50.38, 65.68) |
| High blood pressure | 223 (48.48) | 65.92 (59.44, 71.86) |
| High cholesterol | 17 (3.70) | 70.59 (45.75, 87.23) |
| Multi chronic diseases | 49 (10.65) | 46.94 (33.51, 60.82) |
| Other chronic diseases | 13 (2.83) | 46.15 (22.31, 71.89) |
| Physical activity | ||
| No | 260 (56.5) | 63.46 (57.42, 69.11) |
| Yes | 200 (43.5) | 57.50 (50.53, 64.18) |
| Smoking | ||
| No | 450 (97.83) | 60.89 (56.29, 65.31) |
| Yes | 10 (2.17) | 60.00 (29.67, 84.21) |
| Continuous variables | Mean (SD) | |
| Age | 59.17 (11.59) | |
| Duration of diabetes (years) | 6.42 (5.13) | |
| HbA1C | 7.81 (2.03) | |
| Systolic blood pressure | 121.96 (14.31) | |
| Diastolic blood pressure | 77.13 (8.24) | |
Based on the results of univariate logistic regression, the odds of UDM in patients aged 45–69 was two times of patients aged 24–44 years (95% CI: 1.09–3.66) Increase in education level was associated with lower odds of UDM, however, the association was not statistically significant. Systolic and diastolic blood pressure were associated with increased odds of UDM by two and three% respectively (Table 2). Based on the results of the adjusted model increase in diastolic blood pressure was significantly associated with UDM, that’s means each unit increase in diastolic blood pressure was associated with a 3% increase in UDM (95% CI: 1.01, 1.06), adjusted for age, gender, education, duration of diabetes, and physical activity (Table 3).
Table 2.
univariate analysis of associated factors with UDM
| Variables | OR | P-value | 95% CI |
|---|---|---|---|
| Age group (years) | |||
| 24–44 | 1.00 | ||
| 45–69 | 2.00 | 0.025 | 1.09, 3.66 |
| 70–91 | 1.53 | 0.238 | 0.76, 3.09 |
| Gender | |||
| Male | 1.00 | ||
| Female | 0.99 | 0.978 | 0.65, 1.52 |
| Education | |||
| Illiterate | 1.00 | ||
| Primary | 1.31 | 0.263 | 0.82, 2.11 |
| Intermediate | 0.71 | 0.209 | 0.42, 1.21 |
| Diploma | 0.67 | 0.170 | 0.38, 1.19 |
| Marital status | |||
| Single | 1.00 | ||
| Married | 0.98 | 0.939 | 0.59, 1.61 |
| Physical activity | |||
| No | 1.00 | ||
| Yes | 0.78 | 0.194 | 0.53, 1.14 |
| Body mass index | |||
| < 25 | 1.00 | ||
| 25–30 | 1.14 | 0.606 | 0.69, 1.90 |
| > 30 | 1.42 | 0.204 | 0.83, 2.43 |
| Smoking | |||
| No | 1.00 | ||
| Yes | 0.96 | 0.955 | 0.27, 3.46 |
| Systolic blood pressure | 1.02 | 0.012 | 1.00, 1.03 |
| Diastolic blood pressure | 1.03 | 0.004 | 1.01, 1.06 |
| Duration of diabetes (years) | 1.04 | 0.041 | 1.00, 1.09 |
Table 3.
the adjusted analysis of associated factors with UDM
| Variables | Odds Ratio | p-value | 95% CI |
|---|---|---|---|
| Age group (years) | |||
| 24–44 | 1 | ||
| 45–69 | 1.40 | 0.316 | 0.72, 2.72 |
| 70–91 | 0.95 | 0.897 | 0.42, 2015 |
| Gender | |||
| Male | 1 | ||
| Female | 0.92 | 0.735 | 0.59, 1.46 |
| Education | |||
| Illiterate | 1 | ||
| Primary | 1.30 | 0.304 | 0.79, 2.16 |
| Intermediate | 0.75 | 0.337 | 0.42, 1.34 |
| Diploma | 0.80 | 0.515 | 0.42, 1.55 |
| Diastolic blood pressure | 1.03 | 0.018 | 1.01, 1.06 |
| Duration of diabetes (years) | 1.03 | 0.127 | 0.99, 1.08 |
| Physical activity | |||
| No | 1 | ||
| Yes | 0.81 | 0.302 | 0.54, 1.21 |
Discussion
Based on the results of this study, the prevalence of UDM was more than 60%. Prevalence in Borujerd was more than Rasht and Khodabandeh. Prevalence in patients with a higher level of education was lower than in illiterate and low levels of education. The prevalence of UDM in patients aged 45–69 years old was more than in younger and older patients. The high prevalence of UDM in patients may be due to a lack of access to health services because of high costs, the lifestyle of patients, lack of attention to medical advice in patients, and lack of knowledge regarding complications of UDM. Based on the results of the adjusted model age, education, and diastolic blood pressure were associated with UDM. The odds of UDM in patients aged 45–69 years was 53% more than in patients aged 24–44 years, although this association was not statistically significant. An increase in education level was associated with lower odds of UDM in patients.
Each unit increase in diastolic blood pressure was significantly associated with a 3% increase in odds of UDM.
In another study in Iran, the prevalence of UDM in patients with diabetes in Yazd province was 58.3% [11], which is in line with our results. Results of a study in Pakistan showed that the prevalence of UDM in patients was 39.0% which is lower than our finding, based on the results of this study age, diagnosis location, information sources of patients, diabetes expenditures, the number of tea or coffee cups, and a number of treatments modalities were significantly associated with UDM [10]. The results of this study regarding the association between age and UDM are not in the line with our study. In our study, the odds of UDM in younger patients was lower than in middle-aged patients and older. A reason may be due to better knowledge of younger people than other groups. The high prevalence of UDM in patients with diabetes can lead to major complications such as amputation. One of the main risk factors of amputation in these patients is a lack of HbA1C monitoring and consequently UDM [16]. The prevalence of UDM in patients with a higher level of education was lower than in illiterate and primary level, which may be due to better knowledge and socioeconomic status of these patients and consequently getting better healthcare services. Higher education is related to a healthy lifestyle such as consuming vegetables and fruits, and more physical activities [17]. In addition, the self-care and monitoring of blood glucose in educated patients may be more than low level or uneducated patients [18], therefore it’s expected the prevalence of UDM in educated patients be lower than low level or illiterate patients.
In the study of Jon et al., the average of HbA1C 7.9 was reported, which is similar to the results of our study [19]. Our results did not show any statistical significant association between smoking, BMI, and physical activity with UDM, which may be due to the low power of our study. Although the association of physical activity and UDM in the univariate and adjusted analysis was not statistically significant, the odds of UDM in patients who had physical activity were about 20% lower than in patients without physical activity. The effect of lifestyle intervention including physical activity on blood sugar control is shown in a clinical trial [20], which supports our finding. The negative association of BMI, cigarette smoking, and hookah with UDM is shown in a study [21]. Based on the results of studies diabetes-specific quality of life is associated with HbA1C [22, 23].
Globally prevalence of diabetes in men and women is similar, but in > 70 years old prevalence in men is more than in women [25]. There was no significant difference in the prevalence of UDM between men and women in our study, this finding is in line with another study in Iran [11]. In a study in Pakistan, women were more likely to have MDU than men (OR = 1.54 95% CI: 1.00, 2.38) [10]. The difference between the gender-specific prevalence of UDM between Iran and Pakistan may be due to differences in receive of healthcare by patients. Based on the results of a systematic review in Saudi Arabia, there is controversy among the results of included studies regarding the association between gender and poor glycemic control, in two studies the mean value of HbA1C in men was lower than in women, but in a study, the risk of poor glycemic control in men was 1.4 time than women [24].
Several studies reported the prevalence of UDM among adults aged over 55 years with less exercise, losing muscle mass, and higher weight. As an individual gets old, the function of pancreatic β-cells is reduced. The effect of age on the β-cells function accompanied an impaired insulin sensitivity affected by lifestyle and Comorbidities [25]. The traumatic life events might make people experience Prolonged stressors, leading to an increase in the risk of Pancreatic β-cells dysfunction and insulin secretion [26]. The present study showed that older age, lack of control over risk factors, and low education are all factors that can increase HbA1C levels. Appropriate control of these factors can keep HbA1C at a normal level [27]. Social services, improved access to health services and a healthy lifestyle are all factors that can reduce the prevalence of UDM in developing countries, especially Iran [28].
In this study, we faced limitations. First, patients’ health records were used to extract the required data such as the amount of HbA1C, which in some patients, this test was not performed and therefore was not recorded in the health records. So, we include patient charts with complete recorded data. Second, most of our sample are women, perhaps because women care more about their health and go to health centers more often.
Overall, our findings emphasize the high prevalence of UDM among diabetic patients, therefore considering the major complications of UDM among these patients, planning for effective control of blood glucose sugar is necessary.
Conclusion
The findings of this study indicate that the prevalence of MDU in diabetic patients is high. The prevalence of UDM in patients with a higher level of education was lower than in illiterate and low levels of education. In addition, prevalence in patients aged 45–69 years old was more than in younger and older patients. Diastolic blood pressure and low level of education were associated with UDM in diabetic patients.
Acknowledgements
We would like to thank the deputies of health in Lorestan, Gilan, and Zanjan universities of medical sciences who collaborated in the data collection process.
Funding
This study supported by the Hamadan university of Medical sciences (No. 9905213288).
Declarations
Competing of interest
None.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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