Glycemic Control In Patients Research Articles

Impacts of Extra Virgin Olive Oil Consumption on Glycemic Control in Patients with Metabolic Syndrome

The purpose of this study was to observe the impacts of extra virgin olive oil on glycemic control in patients with metabolic syndrome (MetS). A total number of 70 patients of both genders with MetS were selected with the age varying from 35 to 55 years. Among them, 35 patients who had consumed 25 ml of extra virgin olive oil daily for 12 weeks were included in the study group (Group B). Another 35 patients who did not consume extra virgin olive oil, were enrolled as the control group (Group A) for comparison. Levels of fasting blood glucose (FBG) and glycosylated hemoglobin (HbA1c) were measured in both the control and study groups at baseline and after 12 weeks. EVOO consumption group showed a statistically significant decrease in fasting blood glucose (p =.003) and glycosylated hemoglobin (p <0.001) in comparison to a control group who did not consume extra virgin olive oil. Regular consumption of extra virgin olive oil improves glycemic status in patients with metabolic syndrome.

Relationship between daytime napping with the occurrence and development of diabetes: a systematic review and meta-analysis

ObjectiveTo determine the relationship of napping with incident diabetes risk and glycaemic control in people with diabetes.DesignSystematic review and meta-analysis.Data sourcesMEDLINE (PubMed), EMBASE, Web of Science and the Cochrane Library...

Vitisin B, a resveratrol tetramer from Vitis thunbergii var. taiwaniana, ameliorates impaired glucose regulations in nicotinamide/streptozotocin-induced type 2 diabetic mice.

In Taiwan, Vitis thunbergii var. taiwaniana (VTT) is used in traditional medicine and as a local tea. VTT rich in resveratrol and resveratrol oligomers have been reported to exhibit anti-obesity and anti-hypertensive activities in animal models; however, no studies have investigated type 2 diabetes mellitus (T2DM) treatments. This study aimed to investigate the anti-T2DM effects of resveratrol tetramers isolated from the VTT in nicotinamide/streptozotocin (STZ)-induced Institute of Cancer Research (ICR) mice. The oral glucose tolerance test (OGTT) was used to imitate postprandial blood glucose (BG) regulations in mice by pre-treatment with VTT extracts, resveratrol tetramers of vitisin A, vitisin B, and hopeaphenol 30min before glucose loads. Vitisin B (50mg/kg) was administered to treat T2DM-ICR mice once daily for 28 days to investigate its hypoglycemic activity. Mice pre-treated with VTT-S-95EE, or vitisin B (100mg/kg) 30-min before glucose loading showed significant reductions (P<0.001) in the area under the curve at 120-min (BG-AUC0-120) than those without pre-treatment with VTT-S-95EE or vitisin B. Vitisin B-treated T2DM mice showed hypoglycemic activities via a reduction in plasma dipeptidyl peptidase (DPP)-IV activities to maintain insulin actions and differed significantly than those of untreated T2DM mice (P<0.05), and also reduced BG-AUC0-120 and insulin-AUC0-120 in the OGTT.These invivo results showed that VTT containing vitisin B would be beneficial for developing nutraceuticals and/or functional foods for glycemic control in patients with T2DM, which should be investigated further.

Investigating glycemic control in patients undergoing lower extremity bypass within an enhanced recovery pathway at a single institution: Presented at the Forty-seventh Annual Meeting of the Southern Association for Vascular Surgery, Rio Grande, Puerto Rico, January 18-21, 2023.

Investigating glycemic control in patients undergoing lower extremity bypass within an enhanced recovery pathway at a single institution: Presented at the Forty-seventh Annual Meeting of the Southern Association for Vascular Surgery, Rio Grande, Puerto Rico, January 18-21, 2023.

Challenges of Glycemic Control in Patients with Prader–Willi Syndrome Associated with Congenital Leptin Deficiency

Prader–Willi syndrome (PWS) is a rare multisystem genetic disorder and one of the syndromic causes of childhood obesity. It is characterized by learning difficulties and behavioral challenges with subsequent multiple endocrine and multisystem involvement. Congenital leptin deficiency is also a very rare disorder that causes early-onset obesity with hormonal and metabolic disturbances. In this report, we describe the case of an 11- year- old girl who presented to us with uncontrolled blood sugar, significant weight gain, behavioral disturbances and was diagnosed with PWS with congenital leptin deficiency, type 2 diabetes mellitus, hypothyroidism, hypertension and obstructive sleep apnea. The main purpose of this case report is to describe the barriers of glycemic control and lifestyle modification challenges and implement the optimal management plan in such a rare association.

Association of urinary albumin-to-creatinine ratio with lipid abnormalities and glycemic control in patients with type 2 diabetes mellitus.

While proteinuria aggravates dyslipidemia in diabetic patients, dyslipidemia further worsens proteinuria via inflammatory cytokines-mediated glomerular damage. Urinary albumin creatinine ratio (ACR) is an easy and reliable method of detecting proteinuria. This study aims to determine the association of ACR with lipid abnormalities and glycemic control in the Nepalese population. This was a cross-sectional study conducted among 201 diabetes patients visiting the outpatient department of internal medicine. Based on ACR values, patients were categorized as nonalbuminuric (less than 300μg/mg) or albuminuric (more than 300μg/mg). An unpaired t-test was used to compare the mean of various lipoproteins in these two categories. Binary logistic regression was used to check the association of ACR with sociodemographic factors (age, sex, and education), hypertension, and glycated hemoglobin. Albuminuric patients had higher mean cholesterol (192.8±53.5 vs. 184.2± 37.6; P=0.209), triglyceride (194.9±97.8 vs. 164.4±73.7; P=0.017) and low-density lipoprotein (99.9±38.4 vs. 90.0±27.4; P=0.034) but lower high-density lipoprotein (53.9±18.5 vs. 61.3±19.9; P=0.008) compared to nonalbuminuric patients. There was a significant difference in mean HbA1c values across albuminuria and nonalbuminuria groups (7.1±1.1 vs. 6.7±0.8; OR: 1.4, 95% CI=1.1-1.9, P=0.030). Urine ACR of more than 30mg/gram was associated with higher triglyceride and low-density lipoprotein levels and lower high-density lipoprotein levels. The HbA1c level strongly correlates with the development of albuminuria.

Differences In HbA1c Levels In Diabetes Mellitus Patients Using Capillary And Venous blood Samples

Introduction: HbA1c is a non-enzymatic binding of glucose molecules to hemoglobin through a post- translational glycation process, measuring the level or percentage of glucose bound to hemoglobin, this parameter is used as the main benchmark for controlling Diabetes Mellitus because HbA1c can describe blood sugar levels within a period of 1- 3 months due to red blood cells bound by glucose molecules. HbA1c examination is an examination of glycemic levels which is useful to determine long-term glycemic control in patients with Diabetes Mellitus. From this study to determine differences in HbA1c levels in diabetes mellitus patients using capillary and venous blood samples. Method: Cross-sectional, this research was conducted at the Hematology Laboratory of the Palembang Muhammadiyah Institute of Health and Technology. The population taken was Diabetes Mellitus Patients in the Muhammadiyah Palembang Hospital laboratory. The sample used in this study was 29 samples using purposive sampling. Results: The average HbA1c level was found in 7.91% capillary blood and 7.91% venous blood. Discussion: The conclusion in this study is that capillary and venous blood sampling can be used to check HbA1c levels.

1137 Perioperative Glycaemic Control in Patients Undergoing Major Lower Limb Amputation – How Can We Improve?

Abstract Aim Patients with diabetes undergoing major lower limb amputation (MLLA) have higher rates of unfavourable postoperative outcomes compared to those without diabetes. Inadequate glycaemic management can lead to an increase in wound healing problems, infections, increased length of hospital stay and higher mortality rates. Guidelines from the Vascular Society for Great Britain and Ireland recommend that all MLLA patients should have early input from the Diabetes team. Our study aimed to evaluate local practice in perioperative glycaemic control in MLLA patients at our unit. Method All patients who underwent MLLA between November 2021 and April 2022 were identified by reviewing theatre records. Patient records were reviewed to collect data on diagnosis of diabetes, diabetic medications, capillary blood glucose (CBG) levels on admission, preoperative HbA1c levels, and perioperative and post-operative glycaemic control. Results 33 MLLA were performed (17 AKA, 16 BKA), age range 41 to 85 (mean age 66), 20 male and 13 female patients. 25 patients (76%) were diabetic, 19 patients (58%) had a preoperative HbA1c recorded and all 33 patients had a CBG recorded on admission. 10 diabetic patients (40%) were found to have inappropriate management of their diabetic medication. 18 patients (55%) were identified as having poor glycaemic control on admission (HbA1c &amp;gt;48 or CBG &amp;gt;11.1). Of these, 12 (67%) were reviewed by the Diabetes team. Conclusions Surgical teams must be actively involved in the management of diabetes of their MLLA patients. Patients undergoing MLLA should have HbA1c checked on admission to help identify those who need review by the Diabetes team.

Effects of Nonsurgical Periodontal Therapy on Glycemic Control in Diabetic Patients under Systemic Administration of Antidiabetic Ayurvedic Drug.

This study aimed to monitor the metabolic response of nonsurgical periodontal therapy in type-2 diabetic patients with chronic periodontitis under systemic administration of antidiabetic ayurvedic drug. About 90 newly diagnosed mild-to-moderate forms of type-2 diabetes mellitus (DM) subjects with generalized chronic periodontitis were selected according to the inclusion and exclusion criteria and were randomly divided into group A and group B with 45 patients in each group. Clinical parameters, including plaque index, probing pocket depth, clinical attachment level, and glycemic status, were assessed at baseline. Following initial periodontal clinical examination, the drug Nishamalaki (NA) 2 gm twice daily for 3 months was prescribed after food by an Ayurvedic physician to all the patients enrolled in group A and group B, and scaling and root planing were completed only for group B patients. Patients were recalled for review, and all the parameters were reassessed at the end of the 1st, 2nd, and 3rd months following interventions. Regarding clinical and metabolic parameters at baseline, no statistically significant differences were displayed between the two groups. However, at the 3-months follow-up period, the patients in group B demonstrated significantly better clinical and metabolic outcomes than patients in group A. Periodontal therapy improved glycemic control in patients with type-2 DM in both groups; however, the reduction in FBS values reached statistical significance only in the group receiving scaling and root planing alone. Nonsurgical periodontal therapy may have a beneficial effect on the periodontal clinical and glycemic levels in type-2 diabetic patients with chronic periodontitis.

Does fully closed-loop automated insulin delivery improve glycaemic control in patients with type 2 diabetes? A meta-analysis of randomized controlled trials.

This meta-analysis investigated the efficacy and safety of fully closed-loop automated insulin delivery (AID) in patients with type 2 diabetes. We systemically searched PubMed, Scopus, Web of Science, and Cochrane Central from inception until April 26, 2023. We included randomized controlled trials (RCTs) comparing fully closed-loop AID versus conventional insulin therapy. The outcomes were pooled as the mean difference (MD) and risk ratio with 95% confidence interval (CI) in the random effect model. Our primary outcome was the proportion of time in the target glucose range (5.6-10 mmol/L, 3.9-10 mmol/L, or 3.9-8 mmol/L, depending on the study). Key secondary outcomes included the proportion of time spent in hyperglycaemia or hypoglycaemia. We included seven RCTs (three crossover and four parallel design), compromising 390 patients. Our analysis showed that compared to the control group, fully closed-loop AID increased the proportion of time spent within the target glucose range by additional 337 min per 24 h (MD = 23.39%, 95% CI [16.64%, 30.14%], p < 0.01), additional 108 min overnight (MD = 22.40%, 95% CI [12.88%, 31.91%], p < 0.01), and additional 258 min during the daytime period (MD = 26.85%, 95% CI [21.06%, 32.63%], p < 0.01). Compared to the control group, the overall time in hyperglycaemia was shortened by 326 min per 24 h (MD = -22.67%, 95% CI [-30.87%, -14.46%], p < 0.01). There was no significant difference between the two groups in terms of overall, overnight, and daytime periods spent in hypoglycaemia. Our meta-analysis suggests that fully closed-loop AID may improve glycaemic control in patients with type 2 diabetes, particularly for those with more challenging diabetes management. Further research is required to establish the feasibility of implementing these systems in clinical practice. [Correction added on 26 August 2023 after first online publication: Under Results, the first sentence "We included seven RCTs (three crossover and one parallel designs)" has been changed to "We included seven RCTs (three crossover and four parallel designs)".].

Correlation of HOMA-IR and HbA1C with hematological parameters in patient with Diabetes mellitus Type II in Kirkuk city

Objective: The aim of this study was to investigate the relationship between hematological parameters and glycemic control in patients with type 2 diabetes mellitus (DM). Materials and Methods: This case-control study included 50 patients with DM and 50 healthy controls. Blood samples were collected from all participants to measure various hematological parameters and serum glucose, insulin, and HbA1c levels. Homeostatic Model Assessment-Insulin Resistance (HOMA-IR) was calculated to evaluate insulin resistance. Statistical analysis was performed to compare the results between the groups and to determine the correlation between hematological parameters and glycemic control. Results: The results showed that serum glucose, insulin, HbA1c, serum potassium, RDW, platelet count, and MID were significantly increased in the DM group compared to the control group, while MCV was significantly decreased. The correlation analysis showed that MID, platelet count, PCT count, and PDW were positively correlated with serum glucose, HbA1c, and HOMA-IR, while MCV was negatively correlated with serum glucose and HbA1c. RBC count, RDW, and PCV were positively correlated with HbA1c and HOMA-IR. Conclusions: The study found that DM type II patients had elevated serum glucose, insulin, HOMA IR, and HbA1C levels, as well as increased serum potassium and MID-range absolute count, and decreased MCV but increased RDW. Platelet count, PCT count, and PDW were positively correlated with serum glucose, HbA1C, and HOMA IR. These hematological parameters may serve as useful markers for assessing glycemic control and insulin resistance in DM type II patients.

Dysglycemia and arrhythmias.

Disorders in glucose metabolism can be divided into three separate but interrelated domains, namely hyperglycemia, hypoglycemia, and glycemic variability. Intensive glycemic control in patients with diabetes might increase the risk of hypoglycemic incidents and glucose fluctuations. These three dysglycemic states occur not only amongst patients with diabetes, but are frequently present in other clinical settings, such as during critically ill. A growing body of evidence has focused on the relationships between these dysglycemic domains with cardiac arrhythmias, including supraventricular arrhythmias (primarily atrial fibrillation), ventricular arrhythmias (malignant ventricular arrhythmias and QT interval prolongation), and bradyarrhythmias (bradycardia and heart block). Different mechanisms by which these dysglycemic states might provoke cardiac arr-hythmias have been identified in experimental studies. A customized glycemic control strategy to minimize the risk of hyperglycemia, hypoglycemia and glucose variability is of the utmost importance in order to mitigate the risk of cardiac arrhythmias.

Age and Red Blood Cell Parameters Mainly Explain the Differences Between HbA1c and Glycemic Management Indicator Among Patients With Type 1 Diabetes Using Intermittent Continuous Glucose Monitoring.

Glycated hemoglobin (HbA1c) is the gold standard to assess glycemic control in patients with diabetes. Glucose management indicator (GMI), a metric generated by continuous glucose monitoring (CGM), has been proposed as an alternative to HbA1c, but the two values may differ, complicating clinical decision-making. This study aimed to identify the factors that may explain the discrepancy between them. Subjects were patients with type 1 diabetes, with one or more HbA1c measurements after starting the use of the Freestyle Libre 2 intermittent CGM, who shared their data with the center on the Libreview platform. The 14-day glucometric reports were retrieved, with the end date coinciding with the date of each HbA1c measurement, and those with sensor use ≥70% were selected. Clinical data prior to the start of CGM use, glucometric data from each report, and other simultaneous laboratory measurements with HbA1c were collected. A total of 646 HbA1c values and their corresponding glucometric reports were obtained from 339 patients. The absolute difference between HbA1c and GMI was <0.3% in only 38.7% of cases. Univariate analysis showed that the HbA1c-GMI value was associated with age, diabetes duration, estimated glomerular filtration rate, mean corpuscular volume (MCV), red cell distribution width (RDW), and time with glucose between 180 and 250 mg/dL. In a multilevel model, only age and RDW, positively, and MCV, negatively, were correlated to HbA1c-GMI. The difference between HbA1c and GMI is clinically relevant in a high percentage of cases. Age and easily accessible hematological parameters (MCV and RDW) can help to interpret these differences.

Uncontrolled Diabetes Mellitus during Lockdown period of Covid 19 pandemic

Background: Nepal Government had declared a lockdown from 24th March till 21st July 2020 for prevention and control of spread of Covid 19 pandemic. This has made patients with diabetes mellitus unable to do their physical activity outside home, not able to visit physicians or healthcare workers on time, buy medicines on time, check blood sugar as scheduled. In this study we aimed to study the effect of lockdown on glycemic control of Diabetes patients. Methods: This study was done at National Academy of Medical sciences, Bir Hospital-Endocrine Unit outpatients department. After the ease of lockdown certain patients visited us with past and new reports of Blood glucose and HbA1c. We kept a record of variation of glycemic control, lack of physical activities, continuation of medications and daily food habits. Results: Total of 91 Diabetes Mellitus patients visited our OPD in 3 weeks period after lockdown was eased. 58% were Female and 42 % were Male. Only 7% of patients had good control of Diabetes, 32% had fairly controlled Diabetes and 61% had poorly controlled Diabetes in males. In females 3% had good control of Diabetes, 27% had fairly controlled and 70% had poorly controlled Diabetes. 46-65 age group in both male and female had uncontrolled blood sugar. Among males 49% had increased food habits, 32% had decreased physical activity and 10% of them left or decreased medicine. In similar among females 23% had increased food habits, 39% decreased physical activity, 38% had left or decreased medicines. Conclusion: Lockdown during Covid 19 pandemic had adverse effect on glycemic control of patients. This will lead to further complications of diabetes mellitus. Patients must do normal physical activities. They can do normal exercise inside their house and increase activities with family members in a small area, where possible. We must advice our patients to learn how to perform self glucose monitoring and self adjustment of Insulin and diet. Learning how to access to physicians, healthcare workers and pharmacist through telemedicine is very important during lockdown period.

Behavioral Sleep Interventions and Cardiovascular Risk Factors: Systematic Review and Meta-analysis of Randomized Controlled Trials.

Chronic sleep disturbance has been consistently associated with cardiovascular disease. We sought to determine whether behavioral interventions to improve sleep have been associated with improvements in 4 common cardiovascular disease risk factors: hypertension, diabetes mellitus (DM), obesity, and smoking. Randomized controlled trials evaluating the prospective effect of behavioral sleep interventions on ( a ) blood pressure in participants with hypertension/prehypertension, ( b ) glycemic control in participants with DM/pre-DM, ( c ) anthropometrics in participants who were overweight/obese, and ( d ) smoking status in smokers were eligible. Where feasible, we undertook random-effects meta-analyses of standardized mean differences in cardiovascular disease risk factor change. Overall, 3 trials met the inclusion criteria for blood pressure, 4 for glycemic control, 9 for overweight/obesity, and 2 for smoking. On meta-analysis, interventions with sleep as the sole behavioral target were associated with a significant reduction in hemoglobin A 1c % (-0.84; 95% confidence interval [CI], -1.34 to -0.34), but not a significant reduction in systolic blood pressure (-0.18; 95% CI, -0.55 to 0.20) versus controls. In addition, any interventions with sleep as a behavioral target were associated with significant reductions in hemoglobin A 1c % (-0.71; 95% CI, -1.01 to -0.42) and weight (-0.78; 95% CI, -1.11 to -0.45), but not systolic blood pressure (-0.72; 95% CI, -1.82 to 0.37). Trials evaluating smoking status were not amenable to meta-analysis. Behavioral interventions to improve sleep were associated with improved glycemic control in patients with DM. It is also possible that these interventions improve weight in individuals who were overweight/obese. A low number of trials and small sample sizes indicate that further large, well-designed randomized controlled trials of interventions are warranted.

Intake of Fruit and Glycemic Control in Korean Patients with Diabetes Mellitus Using the Korea National Health and Nutrition Examination Survey.

Despite the well-recognized health benefits of fresh fruit consumption, there is still substantial uncertainty about its potential effects on glycemic control in patients with type 2 diabetes mellitus (T2DM). We examined the association of fresh fruit consumption and glycemic control in patients with T2DM using data from the 6th Korea National Health and Nutrition Examination Survey. The study sample was divided into three groups based on weekly fruit consumption frequency for the analysis. Patients with the highest fruit intake were older than those in the other two groups, and women were more likely to consume fruits in general. Being a current smoker and weekly alcohol intake also showed negative correlations according to the fruit intake tertiles. Fruit consumption was positively correlated with better hemoglobin A1c (HbA1c) levels. Moreover, patients in the highest tertile of fruit intake were 3.48 times more likely to be in good glycemic control defined as HbA1c <7%. We observed that fruit consumption can be helpful in glycemic control in Korean patients with T2DM.

Relationship between Glycemic Control and Triglyceride-Glucose Index in Patients with Type 2 Diabetes Mellitus

The triglyceride-glucose index is a newly discovered parameter that indicates insulin resistance. This study aims to investigate the relationship between the triglyceride-glucose index and triglyceride/high-density lipoprotein ratio with glycemic control in patients with type 2 diabetes mellitus. This study was performed retrospectively in 296 patients with type 2 diabetes mellitus. Patients were divided into two equal groups according to their HbA1c levels as having good glycemic control (HbA1c 7 and below) and poor glycemic control (HbA1c above 7). Age, gender, body mass index, fasting blood glucose, HbA1c, total cholesterol, serum triglyceride level, serum HDL level, serum LDL level, riglyceride-glucose index, and triglyceride/HDL ratio were compared between the groups. Fasting blood glucose, HbA1c, triglyceride, HDL, triglyceride-glucose index, and triglyceride/HDL ratio wassignificantly different between patient groups with good and poor blood glucose regulation (p&lt;0.05). Patients with poor glycemic control had lower fasting blood glucose, HbA1c, triglycerides, triglyceride-glucose index, and HDL values compared to patients with high triglyceride/HDL ratio and good glycemic control. There was no difference between the groups in terms of other variables (p&gt;0.05). Triglyceride-glucose index and triglyceride/HDL ratio may be indicators of poor glycemic control in diabetic individuals. These indices are cheaper, universal, and easy-to-measure parameters compared to HbA1c and can be used to predict glycemic regulation.

Effects of Telephone-Based Brief Motivational Interviewing on Self-Management, Medication Adherence, and Glycemic Control in Patients with Uncontrolled Type 2 Diabetes Mellitus in a Rural Community in Thailand.

Owing to the increased prevalence of type 2 diabetes mellitus (T2DM) and the high proportion of patients with uncontrolled T2DM, effective interventions for disease management are needed. The study aim was to test the effects of brief motivational interviewing (MI) on patients' self-management, medication adherence, and glycemic control. A single-group repeated measures trial was used to examine the effects of usual care only and usual care plus telephone-based brief MI. Participants were 29 patients with uncontrolled T2DM recruited from a rural primary care setting in Nakhon Sawan, Thailand. Participants received usual care during the first 4 weeks, followed by usual care plus brief MI during weeks 4-8. Outcomes of self-management, medication adherence, fasting blood sugar (FBS) levels, and hemoglobin A1c (HbA1c) levels were assessed at baseline, 4 weeks, and 8 weeks. Data were analyzed using descriptive statistics, one-way repeated measures analysis of variance, and Friedman test. Significant changes in self-management (p < 0.001), medication adherence (p < 0.001), and FBS (p < 0.05) were observed over the 8-week study. In multiple comparisons, self-management was the only parameter significantly different across baseline, 4, and 8 weeks (p <0.05, <0.001, and <0.001, respectively); medication adherence was significantly different between 4 and 8 weeks (p < 0.05), and between baseline and 8 weeks (p < 0.001); and FBS was significantly different between 4 and 8 weeks (p < 0.05). HbA1c declined over the 8-week study, but not significantly. An intervention combining telephone-based brief MI with usual care significantly increased self-management, medication adherence, and glycemic control (ie, FBS) after 4 weeks, whereas usual care only significantly increased self-management. Phone-based brief MI may be an effective way for healthcare providers to remotely enhance patients' self-management and glycemic control, thus reducing barriers related to time and geographic location.

Diabetes Self-Care Activities and Their Relationship With Glycemic Control in Patients Visiting Hayatabad Medical Complex, Peshawar.

Background A significant portion of the Pakistani population is affected by diabetes, which has emerged as a global healthcare concern. Objective This study aimed to assess the correlation between glycemic control in diabetes patients and their engagement in diabetes self-care activities (DSCA). Methodology Cross-sectional research was conducted at Hayatabad Medical Complex in Peshawar between June 2019 and May 2020. A total of 280 carefully selected patients with type 2 diabetes mellitus (T2DM) were included. Data collection involved an interviewer-administered questionnaire encompassing sociodemographic information, diabetes-related data, and the summary of the Diabetes Self-Care Activities (SDSCA) scale. Descriptive statistics and Pearson's chi-square test were employed for data analysis. Results The study observed that the majority of participants (40.36%) were females, and the age range of the participants was between 42 and 53 years (68.22%).According to the study, 55.00% of participants had a normal body mass index (BMI), and 71.08% of participants had diabetes in their family. Regarding glycemic control, 55.71% of individuals exhibited good control based on fasting blood sugar (FBS) levelswhile 74.64% showed poor control according to hemoglobin A1C (HbA1c) values. HbA1c was substantially linked with a general diet (healthy eating plan), physical activities, and adherence to medication ((odds ratios (OR): 3.12), (95% confidence interval (CI): 1.02 - 8.78), (P value: 0.031)); ((OR: 2.19, 95%), (CI:1.18 - 3.79), (P value: 0.003)); ((OR: 2.85), (95% CI: 1.22 - 6.59), P value: 0.021)). Conclusion The findings indicated that health professionals need to create health education programs on DSCA in order to increase DSCA adherence in people with T2DM while maintaining glycemic control.

Healthy Lifestyle Score and Glycemic Control in Type 2 Diabetes Mellitus Patients: A City-Wide Survey in China.

Few studies have investigated the combined impact of healthy lifestyle factors on glycemic control. Our study aimed to examine the associations of a healthy lifestyle score (HLS) with glycemic control and to explore the interactive effects of lifestyle factors among patients with type 2 diabetes mellitus (T2DM) in China. This cross-sectional study was conducted among T2DM patients based on the health management of residents from Guangzhou, China. Good glycemic control was defined as fasting plasma glucose < 7.0 mmol/L. HbA1c < 7.0% was also defined as good glycemic control in sensitivity analysis. The HLS was defined as including physical activity, waist circumference, body mass index, dietary habit, smoking, and alcohol consumption. Logistic regression models were used to examine the associations and interactions between the lifestyle factors and glycemic control. Compared with participants with an HLS ≤ 2, the odds ratios (95% confidence intervals) for an HLS of 3, 4, 5, and 6 were 0.82 (0.77-0.87), 0.74 (0.70-0.79), 0.61 (0.57-0.65), and 0.56 (0.53-0.60), respectively. Significant interactions of healthy lifestyle factors in relation to glycemic control were shown (Pinteraction < 0.05). A healthier lifestyle was significantly associated with good glycemic control in patients with T2DM, and combined healthy lifestyle factors had a better effect than considering them individually.