Skip Navigation
Skip to contents

PHRP : Osong Public Health and Research Perspectives



Page Path
HOME > Osong Public Health Res Perspect > Volume 9(4); 2018 > Article
Original Article
Factors that Correlate with Poor Glycemic Control in Type 2 Diabetes Mellitus Patients with Complications
Mohammad Haghighatpanaha, Amir Sasan Mozaffari Nejadb, Maryam Haghighatpanahc, Girish Thungaa, Surulivelrajan Mallayasamya
Osong Public Health and Research Perspectives 2018;9(4):167-174.
Published online: August 31, 2018

aDepartment of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal University, Manipal, India

bNutrition Health Research Center, Student Research Center, Hamadan University of Medical Sciences, Hamadan, Iran

cDepartment of Microbiology, Islamic Azad University, Lahijan Branch, Rasht, Iran

*Corresponding authors: Surulivelrajan Mallayasamy, Department of Pharmacy Practice, Kasturba Hospital, Manipal, Karnataka, India, E-mail: Amir Sasan Mozaffari Nejad, Nutrition Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran, E-mail:
*Corresponding authors: Surulivelrajan Mallayasamy, Department of Pharmacy Practice, Kasturba Hospital, Manipal, Karnataka, India, E-mail: Amir Sasan Mozaffari Nejad, Nutrition Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran, E-mail:
• Received: November 23, 2017   • Revised: June 15, 2018   • Accepted: July 12, 2018

Copyright ©2018, Korea Centers for Disease Control and Prevention

This is an open access article under the CC BY-NC-ND license (

  • 165 Download
  • 60 Crossref
  • 72 Scopus
  • Objectives
    Inadequate glycemic control amongst patients with Type 2 diabetes mellitus (T2DM) indicates a major public health problem and a significant risk factor for the progression and complications caused by diabetes. Glycemic control is the main therapeutic objective for the prevention of organ damage and other complications arising from diabetes.
  • Methods
    This was a retrospective observational study of T2DM patients with complications, who were aged 40 years and older. The study was conducted retrospectively on medical records (in-patient and out-patient) obtained from a South Indian teaching hospital, Manipal, India. The patients included in the study had fasting blood sugar, postprandial blood sugar and HbA1c measured at least twice during follow-ups the previous year. Patients’ HbA1c levels were categorized into good control ≤7% (≤53mmol/mol), and poor control >7% (>53mmol/mol), and patients’ characteristics were analyzed.
  • Results
    A total of 657 patients were included in the study. The mean age was 59.67 (SD = 9.617) years, with 152 (23.1%) females and 505 (76.9%) males, and 514 (78.2%) patients had poor glycemic control. Most of the patients were on insulin mono-therapy [n = 271 (42.1%)], about a third of the patients were on combination therapy that included an oral hypoglycemic agent and insulin [n = 236 (36.6%)]. Patients with a history of more than 10 years of diabetes [n = 293 (44.6%)], had a family history of diabetes [n = 256 (39%)] and obesity [n = 95 (14.5%)], all had poor glycemic control.
  • Conclusion
    This present study indicated a significant association of gender (female), age, high-density lipoprotein level, duration of diabetes and type of medication, with poor glycemic control in T2DM patients that had secondary medical complications.
Diabetes is a chronic condition caused by either an absolute lack of insulin or a relative lack of insulin due to impaired insulin secretion and action [1,2]. Insulin resistance and glucose intolerance results in hyperglycemia and alterations in lipid and protein metabolism [3]. In the long term, these metabolic abnormalities contribute to complications such as cardiovascular disease, retinopathy, nephropathy, and neuropathy [46]. Diabetes mellitus (DM) is very common in all age groups, worldwide [79]. The number of people with diabetes worldwide was estimated as 415 million in 2015, and is expected to rise to 642 million by 2040 [10].
There are several risk factors for the progression of Type 2 DM (T2DM) including family history, obesity, chronic physical inactivity, race or ethnicity, history of impaired fasting glucose, impaired glucose tolerance, HbA1c 5.7% to 6.4% (38.8mmol/mol to 46.4mmol/mol), hypertension, abnormal high-density lipoprotein cholesterol and/or elevated triglyceride levels [11]. The duration of diabetes, lifestyle, level of education, age, number of medications, morbidity, socioeconomic factors and type of insurance coverage, are risk factors for sustained poor glycemic control. Individuals at risk of poor glycemic control may need specific interventions to achieve optimal glycemic control [12].
Inadequate glycemic control among patients with T2DM indicates a major public health issue and a significant risk factor for the progression of diabetic complications. Glycemic control remains the main therapeutic target for prevention of organ damage and other complications arising from diabetes [13]. In clinical practice, achieving optimal glycemic control on a long-term basis is challenging, since the reasons for poor glycemic control in T2DM are complex [14]. Both patient and health care provider-related factors may play a significant role in poor glycemic control [15,16].
The glycosylated hemoglobin, or A1c has become the gold standard for measuring chronic glycaemia and is the clinical marker for predicting long-term complications, particularly microvascular complications [1719]. HbA1c is most commonly measured because it comprises of the majority of glycosylated hemoglobin and is the least affected by recent fluctuations in blood glucose. In epidemiological analyses, glycated hemoglobin (A1c) levels >7% (>53mmol/mol) are associated with a significantly enhanced risk of both macrovascular and microvascular complications, irrespective of the main treatment [2022]. People with diabetes have a greater risk of developing a number of major health problems. The costs related to diabetes include increased use of health services, disability and productivity loss, which can be a considerable burden to the patient, families and society.
T2DM is approaching epidemic levels in India [23]. The level of morbidity and mortality due to diabetes and its possible complications, are enormous and cause significant healthcare problems for both the family and society. Diabetes is associated with a variety of complications and is occurring at a relatively younger age in India [24]. In addition to directly related medical complications, numerous factors contribute to the impact of diabetes on quality of life, morbidity and early death in these patients.
The present study evaluated the factors which predict poor glycemic control as measured by glycosylated hemoglobin. Identifying predictors that contribute to poor glycemic control may enable future therapeutic modification or control of these factors for the management of T2DM.
This retrospective observational study was conducted based on in-patient and out-patient medical records of patients of Kasturba Hospital, Manipal, India. Medical records of patients who were admitted to the hospital during the 2-year time period (from August 2013 to September 2015) who were ≥ 40 years old, diagnosed with T2DM with complications, had fasting blood sugar, post-prandial blood sugar and HbA1c measured at least twice during the previous year, were included in the study.
The study was carried out according to the protocol approved by the Institutional Ethics Committee (IEC: 561/2015). Based on the study criteria and screening of 2,054 patient files, 657 patients who met the study criteria were included in the study.
Every reported visit of the patient to the hospital was followed, and patients’ clinical details were checked until the last visit of the patient. Demographic details like age, sex, occupation, body mass index (BMI), social habits, date of diagnosis of T2DM, number of hospitalizations and clinical parameters, medical and medication history, reports of laboratory investigations, and treatment charts, were all collected and documented in a case report form. For each patient, the mean of the previous two HbA1c levels was calculated and the patients were divided into 2 groups according to the mean HbA1c level, either good control group (HbA1c ≤7% or ≤53mmol/mol) or poor control group (HbA1c >7% or >53mmol/mol). Statistical analyses were carried out using SPSS Ver.20 and p ≤ 0.05 was considered statistically significant. Mean ± SD were used to summarize continuous variables and frequency, and percentage was used to summarize categorical variables. Chi-square test was used to examine the association between categorical variables. The binary logistic regression (univariate and multivariate) model was developed to test the predictors of poor glycemic control. ROC curve was used to check the classification ability of the model.
Out of 657 patients included in this study the mean age was 59.67 (SD = 9.617) years, and 505 (76.9%) were male, and the majority of all study patients were aged 51–70 years [n = 449 (68.3%)]. Most of the patients had a normal weight [n = 302 (46%)], 106 (16.1%) patients were obese (Table 1). Patients were suffering from different types of diabetic complications. Out of 657 patients, 514 (78.2%) had 1 diabetic complication and 143 (21.8%) had 2 complications. The majority of patients [n = 175 (26.6%)] were suffering from diabetic peripheral neuropathy, of which 148 (22.5%) were male, and 27 (4.1%) were female patients. Patients with diabetic retinopathy accounting for 109 (16.6%) males and 48 (7.3%) females. There were 306 (46.6%) patients suffering from cardiovascular disorders, including hypertension and dyslipidemia. In this study, 86 (13.1%) had infectious diseases, which were more common and serious in patients with T2DM. Patients without co-morbidity accounted for 182 (27.7%) patients.
Based on the nature of the patient’s job and physical activity, the study was divided into 5 categories. Most of the patients were physical laborers and houseworker, 46.6% and 21.5% respectively. The remaining were office workers (18.7%) retired (7.5%), or unemployed (5.8%). The majority of the study patients were non-alcoholics [n = 430 (65.4%)] and non-smokers [n = 510 (77.6%)], and 473 (72%) of the patients paid for their own medical care expenses (Table 1).
Over half the study patients 356 (54.2%) had a history of hypertension, 26 (4.0%) had hyperlipidemia, Patients that did not have any history of hypertension or hyperlipidemia accounted for 32.4%. There were 280 (42.6%) patients that used insulin to manage diabetes and 182 (27.7%) had a history of using combination therapy (insulin and oral hypoglycemic drug), 194 (29.5%) had used only oral hypoglycemic agents. One patient that was newly diagnosed for T2DM with complications, and the majority of the patients in the study did not have a history of diabetes in their family. Most of the patients [n = 351 (53.4%)] had been diagnosed with T2DM for more than 10 years. The remaining patients had T2DM for 5–10 years [n = 160 (24.4%)], and 146 (22.2%) had T2DM for less than 5 years (Table 2). Assessment of the drugs prescribed showed that 13 (2%) patients were not prescribed anti-diabetic medication. A combination of insulin and oral hypoglycemic agents were prescribed for 236 (36%) patients to manage their condition. Mostly, patients used insulin to control their blood glucose level [n = 271 (41%)], or oral anti-diabetics as monotherapy [n = 137 (21%)] (Table 2).
There was a significant association between HbA1c levels and demographic factors: gender, age, BMI and occupation. Most of the patients had a HbA1c level >7 % (>53mmol/mol) which represents poor glycemic control in these patients (Table 1). In patients with poor glycemic control, 262 (39.9%) had a history of hypertension, and 147 (22.4%) had a history of insulin and oral anti-diabetics drug prescription. In this study patients either with or without family history of diabetes, had poor glycemic control. There was a significant association between the duration of diabetes and HbA1c levels; 293 (44.6%) patients with poor glycemic control had been suffering from diabetes for more than 10 years. Patients that used insulin alone to control the glucose level accounted for 221 (34.3%) patients, 201 (31.2%) had combination therapy (OHA and insulin), and 396 (60.3%) had 1 or 2 forms of diabetes medication (Table 2).
The risk of poor glycemic control was higher amongst females (OR = 1.86) and patients that were 65 years old or younger, (OR = 1.51) and who were obese (OR = 2.72). House wives were at a higher risk when compared to retired patients (OR = 3.04). Patients with family history were more likely to have poor control [OR = 1.37 (Table 3)]. Patients with a systolic blood pressure greater than 130mmHg were more likely to have poor glycemic control (OR =1.21), patients with a diastolic blood pressure greater than 80mmHg were also more likely to have poor glycemic control (OR = 1.04).
The longer a patient had diabetes the worse the glycemic control; 5 to 10 years duration (OR = 1.74), and in patients with a history of diabetes for more than 10 years compared to those with less than 5 years of illnesss (OR = 2.55). Patients without co-morbidity had significantly better glycemic control compared to patients with co-morbidity (OR=1.56). Other factors like total cholesterol, triglyceride level and the type of diabetes medications, all significantly affected glycemic control (Table 4).
The results of multivariate analysis showed that females (OR = 2.07), patients younger than 65 years old (OR = 1.67), abnormal high-density lipoprotein (HDL) level (OR = 1.72), duration of diabetes (more than 10 years), and type of diabetes medication, were all significantly associated with poor glycemic control (Table 5). The developed logistic regression model included significant variables that are associated with poor glycemic control (HbA1c as reference line). The developed model had an area under ROC curve of 0.683 (p < 0.001).
Diabetes increases the risk of developing a number of major health problems. The level of morbidity and mortality due to diabetes, and its possible long-term complications can cause significant healthcare problems for both the family, and society [25]. Many factors can influence optimal glycemic control: gender, age, BMI, duration of illness, type of medication, lipid profile and blood pressure [26,27]. In this study, HbA1c value was used because it is the gold standard test for glycemic control. In diabetes patients good glycemic control is defined as having values of HbA1c ≤ 7% and poor glycemic control has (HbA1c values of >7% [2830]. A total of 657 patients were included in this study; the majority of the patients had poor glycemic control (78.2%), males were predominant in this study, and a significantly higher risk of poor glycemic control was associated with females (p < 0.001). Roy et al [31] showed escribed sub-optimal control in males.
In this study, a significant association was found between glycemic control and age. Most patients with poor glycemic control belonged to the age categories 50–60 years and 60–70 years, which was similar to the studies reported by Huang et al [32] and Woldu et al [33]. This study observed a significant relationship between glycemic control in diabetic people and BMI (p = 0.014) and occupation (p = 0.042), similar studies by Lee et al [34] and Kassahun et al [35], who reported the effect of being overweight or obese, and occupation in T2DM.
History of hypertension or hyperlipidemia (p = 0.003) and the length of time a person has been diabetic (p < 0.001) were the other factors that were observed in this study to have a significant association with non-glycemic control. Other studies by Khattab et al [36] and Salonen et al [37] reported that a longer duration of diabetes, and both hypertension and dyslipidemia were associated with insulin metabolism disturbance and poor glycemic control. By studying the patients’ medication history and medications prescribed at discharge, a significant association between glycemic control and type of medication history (p = 0.007) was observed. Diabetes medication and the number of diabetic drugs in prescription at discharge was also significantly associated with glycemic control (p < 0.001). This finding is consistent with other studies carried out by Roy et al [31], Agarwal et al [38], Esposito et al [39] and Schweizer et al [40].
In this study, we did not find any statistically significant effects of factors like history of alcohol consumption or smoking, family history and type of medical expenses coverage, with glycemic control. According to another study by Juarez et al [12], the type of insurance coverage did not impact glycemic control significantly. The present study showed that male patients had better glycemic control and the risk of poor glycemic control was significantly higher amongst females and especially in women who are responsible for providing care to the family who may neglect their health care as reported by Kirk et al [41] and Zhao et al [42], the same results were found in this study. It has been observed that patients younger than 65 years old were significantly more likely to have poor glycemic control. Studies by Harrabi et al [43] and Eid et al [44] revealed that age has a significant effect on glycemic control. In a study by Adham et al [45], BMI was reported to impact on HbA1c level. In this study, the significant effects of obesity on poor glycemic control could be explained by impaired insulin resistance and insulin secretion. Another investigation reported by Bays et al [46], confirmed the association of being overweight or obese increase risk of developing diabetes. This study revealed that retired patients had significantly better glucose control compared to house wives and other categories of people. This could have been because retired people have enough time to manage their therapy and change their lifestyle. A survey by Kassahun et al [35], reported that poor glycemic control appeared to be greater amongst farmers compared to unemployed respondents. In the present study, patients who made self-payment for medical expenses appeared to be more likely to have better glycemic control compared to patients with insurance coverage, although this effect was not significant. This is in contrast to the results of a study by Juarez et al [12], where they reported that insurance coverage was not significantly related to glycemic control.
As reported by Papazafiropoulou et al [47] and Bo et al [48], no influence of family history on the clinical characteristics of patients with diabetes was found except for low-density lipoprotein cholesterol levels. In this study, it was observed that patients with a family history of diabetes were more likely to have poor glycemic control, but this effect was not statistically significant. In a study by Khattab et al [36] and Eid et al [44], it has been reported that the duration of T2DM was strongly associated with poor glycemic control. This study revealed similar results, a longer duration of diabetes adversely affected glycemic control, possibly due to a reduction in insulin secretion or excessive insulin resistance in those patients. In addition, a survey reported by Juarez et al [12] showed patients with diabetes for 6 to 7 years, or for 10 years or more were more likely to have wide glycemic variability compared to patients that had diabetes for 3 years or less. A longer duration of diabetes is the risk factor for sustained, poor glycemic control [12].
Lipid abnormalities are common in patients with diabetes. In this study, dyslipidemia was associated with poor glycemic control, especially for higher triglycerides ≥ 150 mg/dL. Studies by Adham et al [45] and Benoit et al [49] revealed that factors related to better glycemic control were lower levels of total cholesterol, low-density lipoprotein cholesterol and triglycerides. In this study, we found that the type of medication was significantly related to the level of HbA1c, in patients receiving insulin + OHA or insulin as mono-therapy were more likely to have poor glycemic control compared to patients who were on oral diabetes medication. This could be due to implementation of an insulin regimen or having an optimal glycemic level that could not be achieved by oral medication alone. The finding is consistent with other reported studies by Khattab et al [36] and Benoit et al [49]. As indicated by El-Kebbi et al [50], co-morbidity does not appear to limit achievement of good glycemic control in patients with T2DM. Patients with more than 1 complication of diabetes appeared to have had better glycemic control compared to patients who were suffering from 1 complication but was not statistically significant. Multivariate analysis indicated a significant association of gender (female), age, HDL level, duration of diabetes illness and type of medication, with poor glycemic control.
The present study showed that there was a significant association between certain demographic factors like gender, age, BMI, occupation and clinical variables like medical history, medication history, triglyceride level, HDL level, duration of diabetes illness, type and number of prescribed diabetes medication, with HbA1c level. Based on these factors, patients at risk of poor glycemic control can be identified, and targeted interventions can be implemented for optimal outcomes. Factors such as level of adherence, physical activity, diabetes education and training programs also impact on the optimal glycemic control, although these factors were not analyzed in this study.

Conflicts of Interest

The authors declare that there was no conflict of interest associated with this paper.

  • 1. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2013;36(Suppl 1). S67−74. PMID: 10.2337/dc13-S067.ArticlePubMed
  • 2. Nolan CJ, Ruderman NB, Kahn SE, et al. Insulin Resistance as a Physiological Defense Against Metabolic Stress: Implications for the Management of Subsets of Type 2 Diabetes. Diabetes 2015;64(3). 673−86. PMID: 10.2337/db14-0694. PMID: 25713189. PMID: 4338588.ArticlePubMedPMC
  • 3. Samuel VT, Shulman GI. The pathogenesis of insulin resistance: integrating signaling pathways and substrate flux. J Clin Invest 2016;126(1). 12−22. PMID: 10.1172/JCI77812. PMID: 26727229. PMID: 4701542.ArticlePubMedPMC
  • 4. Aiello LM. Perspectives on diabetic retinopathy. Am J Ophthalmol 2003;136(1). 122−35. PMID: 10.1016/S0002-9394(03)00219-8. PMID: 12834680.ArticlePubMed
  • 5. Kim NH, Pavkov ME, Knowler WC, et al. Predictive value of albuminuria in American Indian youth with or without type 2 diabetes. Pediatrics 2010;125(4). e844−51. PMID: 10.1542/peds.2009-1230. PMID: 20194283. PMID: 3481836.ArticlePubMedPMC
  • 6. Boulton AJ, Malik RA, Arezzo JC, et al. Diabetic somatic neuropathies. Diabetes Care 2004;27(6). 1458−86. PMID: 10.2337/diacare.27.6.1458. PMID: 15161806.ArticlePubMed
  • 7. Zhao Y, Crimmins EM, Hu P, et al. Prevalence, diagnosis, and management of diabetes mellitus among older Chinese: results from the China Health and Retirement Longitudinal Study. Int J Public Health 2016;61(3). 347−56. PMID: 10.1007/s00038-015-0780-x. PMID: 26755457. PMID: 4880519.ArticlePubMedPMCPDF
  • 8. Bahijri SM, Jambi HA, Al Raddadi RM, et al. The Prevalence of Diabetes and Prediabetes in the Adult Population of Jeddah, Saudi Arabia- A Community-Based Survey. PLoS ONE 2016;11(4). e0152559PMID: 10.1371/journal.pone.0152559. PMID: 4818101.ArticlePubMedPMC
  • 9. International Diabetes Federation [Internet]. International Diabetes Federation: Diabetes India [cited 2016 Apr 10]. Available from:
  • 10. International Diabetes Federation [Internet]. IDF Diabetes 7 ed. Brussels (Belgium): International Diabetes Federation; 2015 [cited 2016 Apr 10]. Available from:
  • 11. American Diabetes Association. Standards for medical care in diabetes. Diabetes Care 2013;36(Suppl 1). S11−66. PMID: 10.2337/dc13-S011.ArticlePubMed
  • 12. Juarez DT, Sentell T, Tokumaru S, et al. Factors associated with poor glycemic control or wide glycemic variability among diabetes patients in Hawaii, 2006–2009. Prev Chronic Dis 2012;9:120065PMID: 10.5888/pcd9.120065.ArticlePubMed
  • 13. Koro CE, Bowlin SJ, Bourgeois N, et al. Glycemic control from 1988 to 2000 among US adults diagnosed with type 2 diabetes a preliminary report. Diabetes Care 2004;27(1). 17−20. PMID: 10.2337/diacare.27.1.17.ArticlePubMed
  • 14. Wallace TM, Matthews DR. Poor glycaemic control in type 2 diabetes: a conspiracy of disease, suboptimal therapy and attitude. QJM 2000;93(6). 369−74. PMID: 10.1093/qjmed/93.6.369. PMID: 10873187.ArticlePubMedPDF
  • 15. Rhee MK, Slocum W, Ziemer DC, et al. Patient adherence improves glycemic control. Diabetes Educ 2005;31(2). 240−50. PMID: 10.1177/0145721705274927. PMID: 15797853.ArticlePubMed
  • 16. Gaster B, Hirsch IB. The effects of improved glycemic control on complications in type 2 diabetes. Arch Intern Med 1998;158(2). 134−40. PMID: 10.1001/archinte.158.2.134. PMID: 9448551.ArticlePubMed
  • 17. Bennett CM, Guo M, Dharmage SC. HbA1c as a screening tool for detection of type 2 diabetes: a systematic review. Diabetic Med 2007;24(4). 333−43. PMID: 10.1111/j.1464-5491.2007.02106.x. PMID: 17367307.ArticlePubMed
  • 18. Larsen ML, Hørder M, Mogensen EF. Effect of long-term monitoring of glycosylated hemoglobin levels in insulin-dependent diabetes mellitus. N Eng J Med 1990;323(15). 1021−5. PMID: 10.1056/NEJM199010113231503.Article
  • 19. Rohlfing CL, Little RR, Wiedmeyer HM, et al. Use of GHb (HbA1c) in screening for undiagnosed diabetes in the US population. Diabetes Care 2000;23(2). 187−91. PMID: 10.2337/diacare.23.2.187. PMID: 10868829.ArticlePubMed
  • 20. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet 1998;352(9131). 837−53. PMID: 10.1016/S0140-6736(98)07019-6. PMID: 9742976.ArticlePubMed
  • 21. The Diabetes Control and Complications Trial Research Group. The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the Diabetes Control and Complications Trial. Diabetes 1995;44(8). 968−83. PMID: 10.2337/diab.44.8.968. PMID: 7622004.ArticlePubMed
  • 22. Stratton IM, Adler AI, Neil HAW, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ 2000;321(7258). 405−12. PMID: 10.1136/bmj.321.7258.405. PMID: 10938048. PMID: 27454.ArticlePubMedPMC
  • 23. Sen S, Chakraborty R, De B, et al. Trends in diabetes epidemiology in Indian population in spite of regional disparities: a systemic review. Int J Diabetes Dev Ctries 2015;35(3). 264−79. PMID: 10.1007/s13410-014-0269-9.ArticlePDF
  • 24. Kaveeshwar SA, Cornwall J. The current state of diabetes mellitus in India. Australas Med J 2014;7(1). 45−8. PMID: 10.4066/AMJ.2014.1979. PMID: 24567766. PMID: 3920109.ArticlePubMedPMC
  • 25. Jeffcoate SL. Diabetes control and complications: the role of glycated haemoglobin, 25 years on. Diabetic Med 2004;21(7). 657−65. PMID: 10.1046/j.1464-5491.2003.01065.x. PMID: 15209755.ArticlePubMed
  • 26. Brown AF, Mangione CM, Saliba D, Sarkisian CA. California Healthcare Foundation/American Geriatrics Society Panel on Improving Care for Elders with Diabetes. Guidelines for Improving the Care of the Older Person with Diabetes Mellitus. J Am Geriatr Soc 2003;51(5 Suppl Guidelines). S265−80. PMID: 10.1046/j.1532-5415.51.5s.1.x. PMID: 12694461.PubMed
  • 27. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 2014;37(Suppl 1). S14−80. PMID: 10.2337/dc14-S014.ArticlePubMed
  • 28. Monnier L, Colette C. Target for Glycemic Control Concentrating on glucose. Diabetes Care 2009;32(Suppl 2). S199−204. PMID: 10.2337/dc09-S310.ArticlePubMedPMC
  • 29. Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Imran SA, Rabasa-Lhoret R, Ross S. Targets for Glycemic Control. Can J Diabetes 2013;37(Suppl 1). S31−4. PMID: 10.1016/j.jcjd.2013.01.016.ArticlePubMed
  • 30. Qaseem A, Vijan S, Snow V, et al. Glycemic Control and Type 2 Diabetes Mellitus: The Optimal Hemoglobin A1c Targets. A Guidance Statement from the American College of Physicians. Ann Intern Med 2007;147(6). 417−22. PMID: 10.7326/0003-4819-147-6-200709180-00012. PMID: 17876024.ArticlePubMed
  • 31. Roy S, Sherman A, Monari-Sparks MJ, et al. Association of comorbid and metabolic factors with optimal control of type 2 diabetes mellitus. N Am J Med Sci 2016;8(1). 31−9. PMID: 10.4103/1947-2714.175197. PMID: 27011945. PMID: 4784181.ArticlePubMedPMC
  • 32. Huang ES, Liu JY, Moffet HH, et al. Glycemic Control, Complications, and Death in Older Diabetic Patients: the Diabetes and Aging Study. Diabetes Care 2011;34(6). 1329−36. PMID: 10.2337/dc10-2377. PMID: 21505211. PMID: 3114320.ArticlePubMedPMC
  • 33. Woldu MA, Wami CD, Lenjisa JL, et al. Factors Associated with Poor Glycemic Control among Patients with Type 2 Diabetes Mellitus in Ambo Hospital, Ambo; Ethiopia. Endocrinol Metab Syndr 2014;3:143.
  • 34. Lee DC, Park I, Jun TW, et al. Physical Activity and Body Mass Index and Their Associations with the Development of Type 2 Diabetes in Korean Men. Am J Epidemiol 2012;176(1). 43−51. PMID: 10.1093/aje/kwr471. PMID: 22547630.ArticlePubMedPDF
  • 35. Kassahun T, Eshetie T, Gesesew H. Factors associated with glycemic control among adult patients with type 2 diabetes mellitus: a cross-sectional survey in Ethiopia. BMC Res Notes 2016;9:78PMID: 10.1186/s13104-016-1896-7. PMID: 26861243. PMID: 4748519.ArticlePubMedPMC
  • 36. Khattab M, Khader YS, Al-Khawaldeh A, et al. Factors associated with poor glycemic control among patients with type 2 diabetes. J Diabetes Complications 2010;24(2). 84−9. PMID: 10.1016/j.jdiacomp.2008.12.008.ArticlePubMed
  • 37. Salonen JT, Lakka TA, Lakka HM, et al. Hyperinsulinemia Is Associated With the Incidence of Hypertension and Dyslipidemia in Middle-Aged Men. Diabetes 1998;47(2). 270−5. PMID: 10.2337/diab.47.2.270. PMID: 9519724.ArticlePubMed
  • 38. Agarwal AA, Jadhav PR, Deshmukh YA. Prescribing pattern and efficacy of anti-diabetic drugs in maintaining optimal glycemic levels in diabetic patients. J Basic Clin Pharm 2014;5(3). 79−83. PMID: 10.4103/0976-0105.139731. PMID: 25278671. PMID: 4160724.ArticlePubMedPMC
  • 39. Esposito K, Chiodini P, Bellastella G, et al. Proportion of patients at HbA1c target <7% with eight classes of antidiabetic drugs in type 2 diabetes: systematic review of 218 randomized controlled trials with 78 945 patients. Diabetes Obes Metab 2012;14(3). 228−33. PMID: 10.1111/j.1463-1326.2011.01512.x.ArticlePubMed
  • 40. Schweizer A, Couturier A, Foley JE, et al. Comparison between vildagliptin and metformin to sustain reductions in HbA1c over 1 year in drug-naïve patients with Type 2 diabetes. Diabet Med 2007;24(9). 955−61. PMID: 10.1111/j.1464-5491.2007.02191.x. PMID: 17509069.ArticlePubMed
  • 41. Kirk JK, Davis SW, Hildebrandt CA, et al. Characteristics associated with glycemic control among family medicine patients with type 2 diabetes. N C Med J 2011;72(5). 345−50.ArticlePubMed
  • 42. Zhao W, Katzmarzyk PT, Horswell R, et al. Sex differences in the risk of stroke and HbA1c among diabetic patients. Diabetologia 2014;57(5). 918−26. PMID: 10.1007/s00125-014-3190-3. PMID: 24577725. PMID: 4141535.ArticlePubMedPMCPDF
  • 43. Harrabi I, Al Harbi F, Al Ghamdi S. Predictors of Glycemic Control among Patients with Type 2 Diabetes in Najran Armed Forces Hospital: A Pilot Study. J Diabetes Mellitus 2014;40(2). 141−7. PMID: 10.4236/jdm.2014.42021.Article
  • 44. Eid M, Mafauzy M, Faridah A. Glycaemic Control of Type 2 Diabetic Patients on Follow Up at Hospital UniversitiSains Malaysia. Malays J Med Sci 2003;10(2). 40−9. PMID: 23386796. PMID: 3561886.PubMedPMC
  • 45. Adham M, Froelicher ES, Batieha A, et al. Glycaemic control and its associated factors in type 2 diabetic patients in Amman, Jordan. East Mediterr Health J 2010;16(7). 732−9. PMID: 10.26719/2010.16.7.732. PMID: 20799529.ArticlePubMedPDF
  • 46. Bays HE, Chapman RH, Grandy S. the SHIELD Investigators’ Group. The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: comparison of data from two national surveys. Int J Clin Pract 2007;61(5). 737−47. PMID: 10.1111/j.1742-1241.2007.01336.x. PMID: 17493087. PMID: 1890993.ArticlePubMed
  • 47. Papazafiropoulou A, Sotiropoulos A, Skliros E, et al. Familial history of diabetes and clinical characteristics in Greek subjects with type 2 diabetes. BMC Endocr Disord 2009;9:12PMID: 10.1186/1472-6823-9-12. PMID: 19397813. PMID: 2680864.ArticlePubMedPMCPDF
  • 48. Bo S, Cavallo-Perin P, Gentile L, et al. Influence of a familial history of diabetes on the clinical characteristics of patients with Type 2 diabetes mellitus. Diabet Med 2000;17(7). 538−42. PMID: 10.1046/j.1464-5491.2000.00330.x. PMID: 10972585.ArticlePubMed
  • 49. Benoit SR, Fleming R, Philis-Tsimikas A, et al. Predictors of glycemic control among patients with Type 2 diabetes: A longitudinal study. BMC Public Health 2005;5:36PMID: 10.1186/1471-2458-5-36. PMID: 15833140. PMID: 1090595.ArticlePubMedPMCPDF
  • 50. El-Kebbi IM, Ziemer DC, Cook CB, et al. Comorbidity and glycemic control in patients with type 2 diabetes. Arch Intern Med 2001;161(10). 1295−300. PMID: 10.1001/archinte.161.10.1295. PMID: 11371257.ArticlePubMed
Table 1
Association of HbA1c levels with demographic factors.
Variable Total patients
N = 657
HbA1c ≤ 7% (≤ 53 mmol/mol) HbA1c > 7% (> 53 mmol/mol) p

N (%) N (%) N (%)
Gender Male 505 (76.9) 121 (18.4) 384 (58.4) 0.013*
Female 152 (23.1) 22 (3.3) 130 (19.8)

Age (y) 40–50 122 (18.6) 26 (4) 96 (14.6) <.001*
51–60 227 (34.6) 43 (6.5) 184 (28)
61–70 222 33.7) 48 (7.3) 174 (26.4)
71–80 74 (11.3) 17 (2.6) 57 (8.7)
> 80 12 (1.8) 9 (1.4) 3 (0.4)

BMI (kg/m2) Underweight 18 (2.7) 3 (0.5) 15 (2.3) 0.014*
Normal 302 (46.0) 70 (10.7) 232 (35.3)
Overweight 231 (35.2) 59 (9.0) 172 (26.2)
Obese 106 (16.1) 11 (1.7) 95 (14.5)

Occupation House work 141 (21.5) 21 (3.2) 120 (18.3) 0.042*
Office work 123 (18.7) 26 (4) 97 (14.7)
Physical labor 306 (46.6) 68 (10.4) 238 (36.2)
Retired 49 (7.4) 17 (2.6) 32 (4.8)
Unemployed 38 (5.8) 11 (1.7) 27 (4.1)

History of alcohol consumption No 430 (65.4) 94 (14.3) 336 (51.1) 0.935
Reformed 227 (34.6) 49 (7.5) 178 (27.1)
Regular 0 0 0

History of smoking No 510 (77.6) 106 (16.1) 404 (61.5) 0.256
Reformed 147 (22.4) 37 (5.6) 110 (16.8)
Regular 0 0 0

Types of payment Insurance 184 (28) 36 (5.6) 148 (22.5) 0.394
Out of pocket 473 (72) 107 (16.3) 366 (55.7)

* p < 0.05 (significant).

BMI = body mass index.

Table 2
Association of HbA1c levels with patient history and therapy.
Variable Total patients
N = 657
HbA1c ≤ 7% (≤ 53 mmol/mol) HbA1c > 7% (> 53 mmol/mol) p

N (%) N (%) N (%)
Medical history HTN 356 (54.2) 94 (14.3) 262 (39.9) 0.003*
Hyperlipidemia 26 (4.0) 5 (0.8) 21 (3.2)
HTN + Hyperlipidemia 62 (9.4) 4 (0.6) 58 (8.8)
No HTN or Hyperlipidemia 213 (32.4) 40 (6.1) 173 (26.3)

Medication history Insulin 282 (42.9) 53 (8.1) 229 (34.9) 0.007*
OHA 194 (29.5) 56 (8.5) 138 (21)
Insulin + OHA 180 (27.4) 33 (5) 147 (22.4)
No drug 1 (0.2) 1 (0.2) 0

Family history No 341 (51.9) 83 (12.6) 258 (39.3) 0.097
Yes 316 (48.1) 60 (9.1) 256 (39)

Duration of diabetes illness (y) < 5 146 (22.2) 49 (7.5) 97 (14.7) < 0.001*
5–10 160 (24.4) 36 (5.5) 124 (18.9)
> 10 351 (53.4) 58 (8.8) 293 (44.6)

Type of antidiabetic drugs at discharge OHA 137 (21.3) 47 (7.3) 90 (14.0) < 0.001*
Insulin 271 (42.1) 50 (7.8) 221 (34.3)
Insulin+ OHA 236 (36.6) 35 (5.4) 201 (31.2)

Number of antidiabetic drugs at discharge No drug 13 (2) 11 (1.7) 2 (0.3) < 0.001*
1–2 509 (77.5) 113 (17.2) 396 (60.3)
3–4 133 (20.2) 19 (2.9) 114 (17.3)
> 4 2 (0.3) 0 2 (0.3)

* p < 0.05 (significant).

HTN = hypertension; OHA = oral hypoglycemic agent.

Table 3
Univariate analysis of demographic factors associated with poor glycemic control.
Variable OR CI (95%) p
Gender Male 1 1.13–3.06 0.014*
Female 1.86

Age (y) > 65 1 1.01–2.25 0.044*
≤ 65 1.51

BMI (kg/m2) < 30 1 1.414–5.23 0.003*
≥ 30 2.72

Occupation House work 3.04 1.44–6.42 0.004*
Office work 1.98 0.95–4.11 0.066
Physical labor 1.86 0.97–3.55 0.060
Retired 1
Unemployed 1.30 0.52–3.26 0.570

Family history No 1 0.94–2.00 0.097
Yes 1.37

Type of payment Out of pocket 1 0.787–1.84 0.394
insurance 1.20

* p < 0.05 (significant).

BMI = body mass index; CI = confidence interval; OR = odd ratio.

Table 4
Univariate analysis of clinical variable associated with poor glycemic control.
Variable OR CI (95%) p
SBP (mmHg) ≤ 130 1 0.83–1.76 0.315
>130 1.21

DBP (mmHg) ≤ 80 1 0.71–1.51 0.829
> 80 1.04

Duration of diabetes (y) < 5 1
5 – 10 1.74 1.0–2.89 0.032*
> 10 2.55 1.64–3.98 < 0.001*

Total cholesterol (mg/dL) < 200 1 0.73–2.30 0.369
≥ 200 1.30

Triglyceride (mg/dL) <150 1 1.03–2.48 0.036*
≥ 150 1.60

HDL (mg/dL) > 45 1 1.03–2.67 0.036*
≤ 45 1.66

Type of diabetes medication OHA 1
Insulin 2.31 1.45–3.68 < 0.001*
OHA + Insulin 3 1.81–4.96 < 0.001*

Number of complication 2 complications 1 0.79–1.89 0.375
1 complication 1.22

Presence of comorbidity Yes 1 1.08–2.27 0.019*
No 1.56

* p < 0.05 (significant).

CI = confidence interval; DBP = diastolic blood pressure; HDL = high-density lipoprotein; LDL = low-density lipoprotein; OR = odd ratio; OHA = oral hypoglycemic agent; SBP = systolic blood pressure.

Table 5
Multivariate analysis of variable associated with poor glycemic control.
Variable OR CI (95%) p
Gender Male 1 1.12–3.82 0.021*
Female 2.07

Age (y) > 65 1 1.0–2.81 0.049*
≤ 65 1.67

BMI (kg/m2) < 30 1 0.97–4.15 0.062
≥ 30 2

Triglyceride (mg/dL) < 150 1 0.84–2.19 0.219
≥ 150 1.35

HDL (mg/dL) > 45 1 1.01–2.95 0.048*
≤ 45 1.72

Duration of diabetes illness (year) < 5 1
5–10 1.35 0.78–2.50 0.344
> 10 2.53 1.46–4.40 0.001*

Diabetes medication OHA 1
Insulin 2.03 1.15–3.58 0.014*
OHA + Insulin 2.41 1.35–4.28 0.003*

Presence of comorbidity Yes 1 0.91–2.27 0.125
No 1.43

* p < 0.05 (significant).

BMI = body mass index; CI = confidence interval; HDL = high-density lipoprotein; OR = odd ratio; OHA = oral hypoglycemic agent.

Figure & Data



    Citations to this article as recorded by  
    • Effectiveness of Family-Based Diabetes Management Intervention on Glycated Haemoglobin Among Adults With Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
      Margareta Teli, Ratsiri Thato, Faizul Hasan, Yohanes Andy Rias
      Biological Research For Nursing.2024; 26(2): 315.     CrossRef
    • Factors linked to poor glycemic control in an outpatient diabetic clinic: a cross-sectional study in Saint-Nicolas Hospital, Haiti
      Ludentz Dorcélus, Emmanuel R. Alexandre, Charnee M. Villemenay, Scaïde U. Benjaminel, Eddie Charles
      Journal of Global Health Reports.2024;[Epub]     CrossRef
    • The prevalence of hypogonadism in male patients with type 2 diabetes mellitus and clinically relevant factors
      Hakan Düğer
      Journal of Health Sciences and Medicine.2024; 7(1): 53.     CrossRef
    • Real-world effectiveness of iGlarLixi in individuals with T2D sub-optimally controlled on oral anti-diabetic drugs with or without basal insulin in daily practice in Saudi Arabia (EMPOWER study)
      Anwar Jammah, Nagwa Roushdy, Mohamed Gamil, Nidal Abu Diab, Naglaa Abdelmonaem, Saher Safarini, Mohamed Gadallah, Nedal Abu Zaid, Yahya Shihadeh, Mohamed Saeed, Jamaa Sadik, Yasser Akil
      Endocrine and Metabolic Science.2024; 15: 100164.     CrossRef
    • Rejuvenating Mobility: Impact of Concurrent Exercise on Functional Claudication Distance and Vascular Health among Patients with T2DM-Associated PAD
      Uroosa Amin, Qurat-ul-Ain Adnan, Dr. Tauseef Ahmad
      Allied Medical Research Journal.2024; : 138.     CrossRef
    • Exploring the Interplay of Socioeconomic and Behavioral Factors: Unraveling Gender Disparities in Glycemic Control Among Adult Type 2 Diabetic Patients in Outpatient Care
      Amar Mankar, Umesh Kawalkar, Nilesh Jadhao, Umesh Joge, Ashutosh Paldiwal, Manoj Talapalliwar, Manoj S Patil
      Cureus.2024;[Epub]     CrossRef
    • Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population
      Ambily Sivadas, S Sahana, Bani Jolly, Rahul C Bhoyar, Abhinav Jain, Disha Sharma, Mohamed Imran, Vigneshwar Senthivel, Mohit Kumar Divakar, Anushree Mishra, Arpita Mukhopadhyay, Greg Gibson, KM Venkat Narayan, Sridhar Sivasubbu, Vinod Scaria, Anura V Kurp
      BMJ Open Diabetes Research & Care.2024; 12(2): e003769.     CrossRef
    • Prevalence of and factors associated with suboptimal glycemic control among patients with type 2 diabetes mellitus attending public hospitals in the Greater Male’ Region, Maldives: a hospital-based cross-sectional study
      Jeehana Shareef, Tawatchai Apidechkul, Peeradone Srichan
      BMC Public Health.2024;[Epub]     CrossRef
    • Exploring the self-efficacy of patients with diabetes: its role as a predictor of diabetes management and well-being
      Ayoub Ali Alshaikh, Faisal Saeed Al-Qahtani, Saif Aboud M. Alqahtani, Ahmad Ali AlFarhan, Ali Mushabbab Al Nuwayhidh, Ayman Mohammed Madkhali, Riyad Saeed AlQahtani, Ali Fayez AlAsmari, Abdulaziz Saeed Alserhani, Hatim Ahmed Alqubaisi, Ziyad Saad Saeed Al
      Frontiers in Endocrinology.2024;[Epub]     CrossRef
    • Dietary glycemic index and glycemic load predict longitudinal change in glycemic and cardio-metabolic biomarkers among old diabetic adults living in a resource-poor country
      Yen Nhi Hoang, Trong Hung Nguyen, Dang Khanh Ngan Ho, Chyi-Huey Bai, Wen-Ling Lin, Huong Duong Phan, Hoang Hiep Phan, Ngoc Luong Tran, Jung-Su Chang
      International Journal of Food Sciences and Nutriti.2024; : 1.     CrossRef
    • Impact of Gender and Age in HbA1c Levels among Libyan Adults Without Known Diabetes in Zeletin City, Libya: A Cross-Sectional Study
      Aisha Zaidi
      AlQalam Journal of Medical and Applied Sciences.2024; : 464.     CrossRef
    • The association between serum high-density lipoprotein and hemoglobin A1c in T2DM: Evidence from a nationwide cross-sectional study in diabetic patients
      Methavee Poochanasri, Sethapong Lertsakulbunlue, Chutawat Kookanok, Ram Rangsin, Wisit Kaewput, Boonsub Sakboonyarat, Mathirut Mungthin, Parinya Samakkarnthai
      Diabetes Epidemiology and Management.2024; 16: 100232.     CrossRef
    • Determinants of poor glycemic control among type 2 diabetes mellitus patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched case-control study
      Gebrehiwot Lema Legese, Getahun Asres, Shitaye Alemu, Tesfaye Yesuf, Yeabsira Aklilu Tesfaye, Tsegaw Amare
      Frontiers in Endocrinology.2023;[Epub]     CrossRef
    • Prevalence of Glycemic Control and Factors Associated With Poor Glycemic Control: A Systematic Review and Meta-analysis
      Zebenay Workneh Bitew, Ayinalem Alemu, Desalegn Abebaw Jember, Erkihun Tadesse, Fekadeselassie Belege Getaneh, Awole Seid, Misrak Weldeyonnes
      INQUIRY: The Journal of Health Care Organization, .2023; 60: 004695802311557.     CrossRef
    • Glycemic control and diabetes complications among adult type 2 diabetic patients at public hospitals in Hadiya zone, Southern Ethiopia
      Abraham Lomboro Dimore, Zerihun Kura Edosa, Asmelash Abera Mitiku, Suman S. Thakur
      PLOS ONE.2023; 18(3): e0282962.     CrossRef
    • Using Machine Learning for the Risk Factors Classification of Glycemic Control in Type 2 Diabetes Mellitus
      Yi-Ling Cheng, Ying-Ru Wu, Kun-Der Lin, Chun-Hung Lin, I-Mei Lin
      Healthcare.2023; 11(8): 1141.     CrossRef
    • Knowledge and Awareness About Diabetes Mellitus Among Urban and Rural Population Attending a Tertiary Care Hospital in Haryana
      Dr.Lalit Kumar, Rahul Mittal, Akhil Bhalla, Ashwani Kumar, Hritik Madan , Kushagra Pandhi, Yukta Garg, Kamaldeep Singh, Arpit Jain, Surya Rana
      Cureus.2023;[Epub]     CrossRef
    • Glycemic Control and Its associated Determinants among Type II Diabetic Patients at Tertiary Care Hospital in North India
      Soorvir singh Gurger, Anshu Mittal, Gauri shankar Goel, Anuj Mittal, Deepmala Kamboj
      Healthline.2023; 14(1): 17.     CrossRef
    • Prevalence of medication adherence and glycemic control among patients with type 2 diabetes and influencing factors: A cross-sectional study
      Budi Suprapti, Zamrotul Izzah, Ade Giriayu Anjani, Mareta Rindang Andarsari, Wenny Putri Nilamsari, Cahyo Wibisono Nugroho
      Global Epidemiology.2023; 5: 100113.     CrossRef
    • The impact of pharmacist interventions, follow-up frequency and default on glycemic control in Diabetes Medication Therapy Adherence Clinic program: a multicenter study in Malaysia
      Phei Ching Lim, Hooi Hoon Tan, Nurul Ain Mohd Noor, Chee Tao Chang, Te Ying Wong, Ee Linn Tan, Chiou Ting Ong, Kalyhani Nagapa, Lee Shyong Tai, Wei Ping Chan, Yong Boey Sin, Yin Shan Tan, Shanty Velaiutham, Rohaizan Mohd Hanafiah
      Journal of Pharmaceutical Policy and Practice.2023;[Epub]     CrossRef
    • Early detection system of risk factors for diabetes mellitus type 2 utilization of machine learning-random forest
      Johannes B. Ginting, Tri Suci, Chrismis N. Ginting, Ermi Girsang
      Journal of Family and Community Medicine.2023; 30(3): 171.     CrossRef
    • Identifying Profiles of Patients With Uncontrolled Type 2 Diabetes Who Would Benefit From Referral to an Endocrinologist
      Eden Avnat, Gabriel Chodick, Varda Shalev
      Endocrine Practice.2023; 29(11): 855.     CrossRef
    • Glycemic control and associated factors among type 2 diabetes mellitus patients: a cross-sectional study of Azar cohort population
      Masoud Faghieh Dinavari, Sarvin Sanaie, Kimia Rasouli, Elnaz Faramarzi, Roghayeh Molani-Gol
      BMC Endocrine Disorders.2023;[Epub]     CrossRef
    • Metabolic Biomarkers in Adults with Type 2 Diabetes: The Role of PPAR-γ2 and PPAR-β/δ Polymorphisms
      Sandra A. Reza-López, Susana González-Gurrola, Oscar O. Morales-Morales, Janette G. Moreno-González, Ana M. Rivas-Gómez, Everardo González-Rodríguez, Verónica Moreno-Brito, Angel Licón-Trillo, Irene Leal-Berumen
      Biomolecules.2023; 13(12): 1791.     CrossRef
    • Estimation of the onset time of diabetic complications in type 2 diabetes patients in Thailand: a survival analysis
      Natthanicha Sauenram, Jutatip Sillabutra, Chukiat Viwatwongkasem, Pratana Satitvipawee
      Osong Public Health and Research Perspectives.2023; 14(6): 508.     CrossRef
    • What drives glycemic control in a person living with diabetes?
      Rajiv Singla, Geetu Gupta, Yashdeep Gupta
      International Journal of Diabetes in Developing Co.2022; 42(2): 369.     CrossRef
    • Prevalence and predictors of suboptimal glycemic control among patients with type 2 diabetes mellitus in northern Thailand: A hospital-based cross-sectional control study
      Fartima Yeemard, Peeradone Srichan, Tawatchai Apidechkul, Naphat Luerueang, Ratipark Tamornpark, Suphaphorn Utsaha, Sompop Bencharit
      PLOS ONE.2022; 17(1): e0262714.     CrossRef
    • Exploring of Determinants Factors of Anti-Diabetic Medication Adherence in Several Regions of Asia – A Systematic Review
      Much Ilham Novalisa Aji Wibowo, Nanang Munif Yasin, Susi Ari Kristina, Yayi Suryo Prabandari
      Patient Preference and Adherence.2022; Volume 16: 197.     CrossRef
    • Visual impairment and its predictors among people living with type 2 diabetes mellitus at Dessie town hospitals, Northeast Ethiopia: institution-based cross-sectional study
      Mohammed Abdu Seid, Adugnaw Ambelu, Mengistie Diress, Yigizie Yeshaw, Yonas Akalu, Baye Dagnew
      BMC Ophthalmology.2022;[Epub]     CrossRef
    • Relations of Well-Being, Coping Styles, Perception of Self-Influence on the Diabetes Course and Sociodemographic Characteristics with HbA1c and BMI Among People with Advanced Type 2 Diabetes Mellitus
      Agnieszka Łukasiewicz, Andrzej Kiejna, Ewelina Cichoń, Aleksandra Jodko-Modlińska, Marcin Obrębski, Andrzej Kokoszka
      Diabetes, Metabolic Syndrome and Obesity: Targets .2022; Volume 15: 407.     CrossRef
    • A bibliometric analysis of highly cited insulin resistance publications in Science Citation Index Expanded
      Yuh-Shan Ho, Priyanga Ranasinghe
      Obesity Medicine.2022; 31: 100399.     CrossRef
    • Alternate-day add-on therapy with dapagliflozin in patients with type 2 diabetes mellitus: potential benefits and concerns
      Harmanjit Singh, Dinesh Joshi, Seerat Narula, Mandeep Singla, Ravi Rohilla, Jagjit Singh
      Expert Review of Clinical Pharmacology.2022; 15(2): 197.     CrossRef
    • Factors associated with Glycemic control among Syrian patients with Type 2 Diabetes Mellitus
      Khadija Khalil, Afraa Zrieki`
      Research Journal of Pharmacy and Technology.2022; : 1701.     CrossRef
    • A Comparative analysis of type 2 diabetes management quality indicators in cancer survivors
      Eun J. Ko, Su J. Lee
      Asia-Pacific Journal of Oncology Nursing.2022; 9(11): 100116.     CrossRef
    • Analysis of the Association between Metabolic Syndrome and Renal Function in Middle-Aged Patients with Diabetes
      Yoonjin Park, Su Jung Lee
      International Journal of Environmental Research an.2022; 19(18): 11832.     CrossRef
    • Effective data-driven precision medicine by cluster-applied deep reinforcement learning
      Sang Ho Oh, Su Jin Lee, Jongyoul Park
      Knowledge-Based Systems.2022; 256: 109877.     CrossRef
    • Management goal achievements of diabetes care in Iran: study profile and main findings of DiaCare survey
      Gita Shafiee, Safoora Gharibzadeh, Nekoo Panahi, Farideh Razi, Seyed Masoud Arzaghi, Vahid Haghpanah, Afshin Ostovar, Alireza Raeisi, Alireza Mahdavi-Hezareh, Bagher Larijani, Ensieh Nasli Esfahani, Ramin Heshmat
      Journal of Diabetes & Metabolic Disorders.2022; 22(1): 355.     CrossRef
    • Glycemic control and its determinants among people with type 2 diabetes mellitus in Ernakulam district, Kerala
      ShanaShirin Najeeb, TeenaMary Joy, Aswathy Sreedevi, K Vijayakumar, Syama, . Glycaemic Control and Determinants Team
      Indian Journal of Public Health.2022; 66(5): 80.     CrossRef
    • Sex Differences in the Effects of CDKAL1 Variants on Glycemic Control in Diabetic Patients: Findings from the Korean Genome and Epidemiology Study
      Hye Ah Lee, Hyesook Park, Young Sun Hong
      Diabetes & Metabolism Journal.2022; 46(6): 879.     CrossRef
    • Relationship and influences of behavioral and psychological factors on metabolic control of patients with type 2 diabetes mellitus
      Vojislav Stanojevic, Marija Jevtic, Milena Mitrovic, Marko Panajotovic, Aleksandar Aleksic, Cedomirka Stanojevic
      Vojnosanitetski pregled.2022; 79(12): 1177.     CrossRef
    • Lipid Profile and Glycemic Control in Type 2 Diabetic Patients
      Sarah Maan AL-Bahrani, Batool A.Gh. Yassin
      Arab Board Medical Journal.2022; 23(1): 21.     CrossRef
    • Glycemic Control of Diabetes Mellitus Patients in Referral Hospitals of Amhara Region, Ethiopia: A Cross-Sectional Study
      Berhanu Elfu Feleke, Teferi Elfu Feleke, Melkamu Beyene Kassahun, Wondemu Gebrekirose Adane, Netsanet Fentahun, Abel Girma, Alamirew Alebachew, Eyaya Misgan, Hanna Demelash Desyibelew, Mulat Tirfie Bayih, Omer Seid, Daniel Diaz
      BioMed Research International.2021; 2021: 1.     CrossRef
    • Association of glycemic control and anthropometric measurement among type 2 diabetes mellitus: a cross-sectional study
      Mitku Mammo Taderegew, Mamo Solomon Emeria, Betregiorgis Zegeye
      Diabetology International.2021; 12(4): 356.     CrossRef
    • Impact of pharmacist-led educational intervention on predictors of diabetic foot at two different hospitals of Malaysia
      AmerHayat Khan, MuhammadZahid Iqbal, SyedAzhar Syed Sulaiman, Aznita Ibrahim, NorShaffinaz Binti Yusoff Azmi, MuhammadShahid Iqbal, AhmedA Albassam
      Journal of Pharmacy And Bioallied Sciences.2021; 13(1): 108.     CrossRef
    • Factors Associated with Glycaemic Control among Diabetic Patients Managed at an Urban Hospital in Hanoi, Vietnam
      Luu Quang Thuy, Hoang Thi Phuong Nam, Tran Thi Ha An, Bui Van San, Tran Nguyen Ngoc, Le Hong Trung, Pham Huy Tan, Nguyen Hoang Thanh, Everson A Nunes
      BioMed Research International.2021; 2021: 1.     CrossRef
    • Predictors of Poor Plasma Glucose Maintenance in Type II Diabetic People with Ophthalmic Complication: The Case of Dessie Hospitals in Ethiopia
      Mohammed Abdu Seid, Baye Dagnew
      Diabetes, Metabolic Syndrome and Obesity: Targets .2021; Volume 14: 2317.     CrossRef
    • Oral health and longitudinal changes in fasting glucose levels: A nationwide cohort study
      Tae-Jin Song, Yoonkyung Chang, Jimin Jeon, Jinkwon Kim, David M. Ojcius
      PLOS ONE.2021; 16(6): e0253769.     CrossRef
    • Poor Glycemic Control and Its Contributing Factors Among Type 2 Diabetes Patients at Adama Hospital Medical College in East Ethiopia
      Tewodros Yosef, Dejen Nureye, Eyob Tekalign
      Diabetes, Metabolic Syndrome and Obesity: Targets .2021; Volume 14: 3273.     CrossRef
    • Probucol Pharmacological and Bio-Nanotechnological Effects on Surgically Transplanted Graft Due to Powerful Anti-Inflammatory, Anti-Fibrotic and Potential Bile Acid Modulatory Actions
      Armin Mooranian, Corina Mihaela Ionescu, Susbin Raj Wagle, Bozica Kovacevic, Daniel Walker, Melissa Jones, Jacqueline Chester, Thomas Foster, Edan Johnston, Momir Mikov, Marcus D. Atlas, Hani Al-Salami
      Pharmaceutics.2021; 13(8): 1304.     CrossRef
    • Clinical pharmacists education and counselling in patients with co-morbid hypertension and diabetes in a Municipal hospital in Ghana
      A. O. Kwakye, K. O. Buabeng, N. A. M. Opare-Addo, E. Owusu-Dabo
      African Journal of Pharmacy and Pharmacology.2021; 15(10): 183.     CrossRef
    • Effect of educational interventions on knowledge of the disease and glycaemic control in patients with type 2 diabetes mellitus: a systematic review and meta-analysis of randomised controlled trials
      Wondimeneh Shibabaw Shiferaw, Tadesse Yirga Akalu, Melaku Desta, Ayelign Mengesha Kassie, Pammla Margaret Petrucka, Yared Asmare Aynalem
      BMJ Open.2021; 11(12): e049806.     CrossRef
    • Persistent Cardiometabolic Health Gaps: Can Therapeutic Care Gaps Be Precisely Identified from Electronic Health Records
      Xiaowei Yan, Walter F. Stewart, Hannah Husby, Jake Delatorre-Reimer, Satish Mudiganti, Farah Refai, Andrew Hudnut, Kevin Knobel, Karen MacDonald, Frangiscos Sifakis, James B. Jones
      Healthcare.2021; 10(1): 70.     CrossRef
    • Glycemic control and awareness of foot care indiabetic foot syndrome
      Ayten Guner Atayoglu, Ali Timucin Atayoglu, Rahime Ozgur, Hammad Khan
      INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine).2021; 17(3): 200.     CrossRef
    • Раннє призначення інсуліну при цукровому діабеті 2-го типу: плюси і мінуси
      S.V. Jargin
      INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine).2021; 17(2): 169.     CrossRef
    • Salutogenic model of health to identify turning points and coping styles for eating practices in type 2 diabetes mellitus
      C. M. M. Polhuis, L. Vaandrager, S. S. Soedamah-Muthu, M. A. Koelen
      International Journal for Equity in Health.2020;[Epub]     CrossRef
    • Self-Care in Adults with Type 2 Diabetes Mellitus: A Systematic Review
      Rebeca Barbosa da Rocha, Cristiano Sales Silva, Vinícius Saura Cardoso
      Current Diabetes Reviews.2020; 16(6): 598.     CrossRef
    • Medication adherence assessment among patients with type 2 diabetes mellitus treated polytherapy in indonesian community health center: A cross sectional-study
      Nora Wulandari, Maifitrianti Maifitrianti, Faridlatul Hasanah, Sri Atika, Risa Dini Putri
      Journal of Pharmacy And Bioallied Sciences.2020; 12(6): 758.     CrossRef
    • Glycemic Control Among People Living with Diabetes and Human Immunodeficiency Virus in Ethiopia: Leveraging Clinical Care for the Looming  Co-Epidemics

      Tsegaye Melaku, Legese Chelkeba, Zeleke Mekonnen, Kabaye Kumela
      Diabetes, Metabolic Syndrome and Obesity: Targets .2020; Volume 13: 4379.     CrossRef
    • Electronic medical records-based comparison of glycemic control efficacy between sulfonylureas and dipeptidyl peptidase-4 inhibitors added on to metformin monotherapy in patients with type 2 diabetes
      Suhrin Lee, SeungHwan Lee, In-Jin Jang, Kyung-Sang Yu, Su-jin Rhee
      Translational and Clinical Pharmacology.2020; 28(4): 199.     CrossRef
    • Poor-Glycaemic-Control Prevalence and Determinants among Type 2 Diabetes Mellitus Patients Attending a Primary Health Care Setting in Central Kerala
      Sajith Kumar Soman, Binu Areekal, Sudhiraj Thiruthara Sukumaran, Safa Puliyakkadi, Rajesh Koothupalakkal Ravi
      Journal of Evidence Based Medicine and Healthcare.2020; 7(49): 2892.     CrossRef

    • PubReader PubReader
    • Cite
      export Copy
    • XML DownloadXML Download

    PHRP : Osong Public Health and Research Perspectives