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India has over half a million diabetics, with many others at risk. The Indian Diabetes Risk Score (IDRS) is a simple and validated tool used for mass screening of diabetes mellitus type 2 at the community level. This study assessed the vulnerability of developing diabetes in adults of a rural community of West Bengal using the IDRS and finds out the relationship of the risk of developing diabetes with socioclinical variables.

Multi-stage sampling was employed to select one eligible nondiabetic adult from selected families residing in the rural field practice area of a medical college in West Bengal. They were interviewed with a predesigned and pretested data collection schedule and examined.

Among 197 participants, 83.8% were female, 51.8% were illiterate and 57.4% came from Class IV of Prasad's socioeconomic scale. Of participants, 22.8% had existing known morbidities, and 23.9% had some form of substance addiction. In total, 46.8% of the participants on whom the IDRS could be applied (n = 175) were at high risk of developing diabetes (Score = 60). Gender and existing comorbidities significantly predicted a high risk of diabetes.

A large proportion of the Indian population yet to be diagnosed with diabetes are at a high risk of having the disease. Early detection of the disease can help curtail its complications and reduce its clinical, social and economic burden. Mass screening tools like the IDRS thus become a very important tool in India's attempts to fight diabetes.

Diabetes is a chronic disease and the major types of diabetes are type 1 and type 2. On aging, people with diabetes tend to have long-term problems in hypertension, coronary artery disease, obesity, and nerves. Given the increasing number of complications in recent years, by 2040, 624 million people will have diabetes worldwide and l in 8 adults will have diabetes in the future. Machine learning (ML) is evolving rapidly, many aspects of medical learning use ML. In this study, tension-type headaches (TTH) were associated with diabetes using SPSS, Pearson correlation, and ANOVA tests. Data were collected from Delhi NCR Hospital. It contains 30 diabetic subjects. The purpose of this study was to correlate diabetes analysis from TTH and other diseases using the latest technologies to analyze the Internet of Things and Big Data and Stress Correlation (TTH) on human health. The authors used Pearson correlation to correlate study variables and see if there was any effect between them. There was an important relationship between the percent variable, the total number of individuals, the number of individuals, and the minimum variable. The age (field) of the number of individuals to one of the total number of individuals showed a strong correlation (1.000) with a significant value of p (1.000). Overall, cases of TTH increased with age in men and do not follow the pattern of change in diabetes with age, but in cases of TTH, patterns of headaches such as diabetes increase to age 60 and then tend to decrease.

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy. GDM is defined as glucose intolerance of variable severity with onset or first recognition during pregnancy. The purpose of this paper is to produce information on prevalence, screening and diagnosis, pathophysiology and dietary, medical and lifestyle management of GDM.

This literature review aimed to document and record the results of the most updated studies published dealing with dietary, medical and lifestyle factors in managing GDM.

The prevalence of GDM differs worldwide based on population characteristics, race/ethnicity and diagnostic criteria. The pathophysiology of GDM is multifactorial and it is likely that genetic and environmental factors are associated with the occurrence of GDM. Medical nutritional therapy remains the mainstay of GDM management and aerobic and resistance physical activities are helpful adjunctive therapy when euglycemia is not attained by the medical nutritional therapy alone. When diet and exercise fail to achieve glycemic control, pharmacological agents such as insulin therapy and oral hypoglycemic medications are prescribed. Plasma glucose measurement is an essential part of glycemic control during pregnancy, as well as glycemic control can be evaluated using indicators of glycemic control such as hemoglobin A1c (HbA1c), glycated albumin and fructosamine.

This review is a comprehensive review that illustrates the effect of healthy diet, medical therapy and lifestyle change on improving GDM condition.

This paper discusses the role played by social determinants of health in the incidence and management of type 2 diabetes mellitus (diabetes) among vulnerable populations. This issue is especially important in light of recent data from Statistics Canada indicating that mortality rates from diabetes have been increasing among Canadians since the mid‐1980s, with increases being especially great among those living in low‐income communities. Diabetes therefore appears – like cardiovascular disease – to be an affliction more common among the poor and excluded. It also appears to be especially likely to afflict poor women. Yet we know little about how these social determinants of health influence diabetes incidence and management. What evidence is available is provided and the case is made that the crisis in diabetes requires new ways of thinking about this disease, its causes, and its management.

The purpose of this study is to examine the acute toxicity and antidiabetic activity of Asystacia gangetica leaf ethanol extract.

The study was designed as completely randomized in vivo experimental model. Where acute toxicity study was carried out using 30 albino mice, randomly assigned into six groups of five mice each. Toxicity signs and mortality were observed in the rats within a period of 24 h. The acute and sub-acute antidiabetic study was carried out using 50 rats, randomly assigned into five groups of 10 rats each. The rats’ blood glucose levels were determined and used to assess the acute and sub-acute antidiabetic activity of the extract.

Results obtained from the acute toxicity study indicated no death in any of the study groups, even at 5,000 mg/kg body weight and showed no signs of toxicity. The acute antidiabetic study showed that treatment with 400 mg/kg of the extract significantly (p = 0.01) lowered glucose level in the diabetic rats from 430.6 to 177.4 mg/dl while 800 mg/kg brought down glucose level from 370 to 144.2 mg/dl by the end of 6 h following administration when compared with the diabetic control group. It was observed that the effect of the extract mostly at 800 mg/kg also compared favorably with that of the standard drug (glibenclamide), which lowered glucose level in diabetic rats from 374.2 to 176.4 mg/dl. Furthermore, the significant reduction was evident from 4, 2 and 2 h for 400 mg/kg extract, 800 mg/kg extract and 5 mg/kg glibenclamide, respectively. At sub-acute level the blood glucose was lowered from 155.6 to 127.2 mg/dl, 137 to 124.4 mg/dl and 151.8 to 121.8 mg/dl for diabetic rats treated with 400 mg/kg, 800 mg/kg and 5 mg/kg glibenclamide, respectively, when compared to the diabetic untreated rats, which ranged from 417.6 to 358.6 mg/dl. The biochemical profile, lipid profile and hematological examination were all positively restored near to normal with the herbal treatment at the different doses. At histopathology level, the liver of the rats treated with 400 mg/kg had moderate portal inflammation without interface or lobular hepatitis while that of 800 mg/kg showed severe portal inflammation with the interface and lobular hepatitis with extensive confluents necrosis. The pancreatic cells of the treated rat showed no significant difference in the β-cells of the islets of Langerhans with hyperplasia of the acinar cell when compared to the diabetic untreated.

The record of no death and signs of toxicity implies that the extract is safe for consumption even at a high dosage of 5,000 mg/kg body weight. The significant (p = 0.01) reduction in the plasma glucose level of the treated rats as compared to the control is an indication of blood glucose-lowering potential of the extract at two different doses. The significant reduction evident of the extract at different hours and days for the two doses implies that the extract rate of lowering potentials is dose-dependent. The evidence of moderate-severe portal inflammation with the interface and lobular hepatitis at 800 mg/kg treatment is an indication that the intake of this herb at high dosage for long period is not safe for the liver tissue.

The outcome of this study suggested that the Asystacia gangetica should also be used as a vegetable in-home food preparation and food processing to use its antidiabetic effect. The herbal extract could also be incorporated into a food product and processed into herbal tea bag for convenient. The subjection of this herbal plant to heat treatment during processing could be a possible avenue to make it safe.

The economic burden and complications of diabetes mellitus management will be reduced if the practical implication of this research finding is implemented in foods as vegetable and in functional food production.

This study revealed that Asystacia gangetica leaf extract may be safe and effective for use at a low dose for acute management of diabetes mellitus. This research may be of value to those living with diabetes mellitus.

Machine Learning is an intelligent methodology used for prediction and has shown promising results in predictive classifications. One of the critical areas in which machine learning can save lives is diabetes prediction. Diabetes is a chronic disease and one of the 10 causes of death worldwide. It is expected that the total number of diabetes will be 700 million in 2045; a 51.18% increase compared to 2019. These are alarming figures, and therefore, it becomes an emergency to provide an accurate diabetes prediction.

Health professionals and stakeholders are striving for classification models to support prognosis of diabetes and formulate strategies for prevention. The authors conduct literature review of machine models and propose an intelligent framework for diabetes prediction.

The authors provide critical analysis of machine learning models, propose and evaluate an intelligent machine learning-based architecture for diabetes prediction. The authors implement and evaluate the decision tree (DT)-based random forest (RF) and support vector machine (SVM) learning models for diabetes prediction as the mostly used approaches in the literature using our framework.

This paper provides novel intelligent diabetes mellitus prediction framework (IDMPF) using machine learning. The framework is the result of a critical examination of prediction models in the literature and their application to diabetes. The authors identify the training methodologies, models evaluation strategies, the challenges in diabetes prediction and propose solutions within the framework. The research results can be used by health professionals, stakeholders, students and researchers working in the diabetes prediction area.

Diabetes mellitus is becoming a growing concern worldwide. Hence, the purpose of this study is to assess the magnitude of poor glycemic control and to identify the determinants of poor glycemic control among diabetic patients attending a tertiary care hospital in Bangladesh.

This cross-sectional study was conducted among 732 diabetes patients seeking care at the outpatient department of Bangladesh Institute of Health Sciences Hospital, Dhaka, Bangladesh. Information, including glycemic status, was collected from patients’ medical records using a structured questionnaire.

About 87.6% of the patients were found to have poor glycemic control (glycosylated hemoglobin = 7%). Variables that were significant in bivariate analysis were put into a multivariate model where the factors associated with poor glycemic control were patients aged 41–60 years (odds ratio (OR)=2.26; 95% confidence interval (CI): 1.19–4.32, p = 0.013), suffering from diabetes for > 7 years (OR = 1.84; 95% CI: 1.12–2.99, p = 0.015), using insulin (OR = 2.34; 95% CI: 1.23–4.47; p = 0.010) or diet alone (OR = 0.20; 95% CI: 0.05–0.80, p = 0.023) as a type of diabetes treatment and proper use of medicine (OR = 0.37; 95% CI: 0.17–0.82, p = 0.015).

The high prevalence of poor glycemic control among diabetic patients is evident; therefore, strategic management and proper attention focusing on the predictors of poor glycemic control are necessary to reduce the long-term complications of diabetes.

This study was designed to assess the risk factors associated with hypertension (HTN) and diabetes among artisans in Ogun State, Nigeria. Evidences suggest increasing prevalence, incidences and morbidity of diabetes and HTN in Nigeria. However, the purpose of this study is to plan and prioritize effective intervention programs, there is need to provide data on the prevalence and risk factors for HTN and diabetes among local groups.

In total 300 apparently healthy artisans who have never been diagnosed of diabetes or HTN were randomly selected from five communities. A structured questionnaire was used in obtaining information on the personal characteristics of the respondents. An adapted dietary habit and lifestyle questionnaire were used to assess the dietary habits and lifestyle of the respondents. The WHO global activity questionnaire was adapted and used to gather information on the physical activity level of the respondents. Random blood glucose, blood pressure and anthropometric measurements were assessed using standard instruments. Chi-square (χ²), correlations and multinomial logistic regression analysis were performed to identify significant determinants of diabetes and HTN.

Mean age was 34.8 ± 9.9 and prevalence of diabetes and pre-diabetes were 1 and 4.7 per cent, respectively, while HTN and pre-HTN were 48.0 and 30.3 per cent, respectively. About half (55.7 per cent) of the respondents skip at least a meal daily and 31 per cent snack daily. Most (61.4 per cent) consume alcohol and 65.7 per cent engage in high physical activity. Abdominal obesity was significantly higher among women (p = 0.004). Using the chi-square analysis, age, abdominal obesity and educational status were factors found to be significantly associated with diabetes (p = 0.002; p = 0.007; p = 0.004) while age, gender, abdominal obesity and alcohol consumption had significant association with HTN. Although not statistically significant, respondents were 0.8, 1.0 and 1.1 times more likely to be diabetic with increasing body mass index, waist circumference (WC) and age (odd ratio (OR) = 0.78; confidence intervals (CI): 0.51-1.18; OR = 1.04; CI: 0.89-1.21; OR = 1.06; CI: 0.96-1.18, respectively). Abdominal obesity was significantly associated with HTN (OR = 1.08; CI: 1.03-1.13; p = 0.001). Also, older respondents were 1.1 times more likely of becoming hypertensive (OR = 1.07; CI: 1.02-1.11; p = 0.003). Increased risk of diabetes and HTN was found among respondents with increasing age and WC.

This study was cross-sectional in design; it cannot be used to establish a cause-effect relationship between diabetes, HTN and the observed variables (anthropometric characteristics, dietary habits and lifestyle risk factors). Because of the few numbers (1 per cent) of respondents identified to be diabetic several important risk factors could not be included in the model.

An understanding of the risk factors associated with diabetes and HTN among sub-groups in the population will help to plan effective interventions targeted at specific groups.

The findings of this study show the associated risk factors for diabetes and HTN among artisans in Ogun State.

The purpose of this paper is to provide a comprehensive overview that demonstrates the prevention role of dietary fiber in type2 diabetes. Due to the frequent incidences of type2 diabetes and its related complications, a small percentage of reduction in the cases could save thousands of lives and economic loss spending on healthcare and medication.

A literature review has been performed over the electronic databases Medline PubMed and SciELO (The Scientific Electronic Library Online). The reference list of identified articles has also been reviewed. For this search, the following descriptors were considered: diabetes mellitus, hyperglycemia, diet therapy, dietary fiber and insulin sensitivity.

The updated publications indicated that valuable efforts have been done to clarify the beneficial effect of dietary fiber consumption on type2 diabetes. Dietary fiber plays a role as a promising alternative therapeutic means toward type2 diabetes mellitus prevention.

This review is unique in its comprehensive nature. This paper will reflect the role and mechanism of dietary fiber in the prevention of type2 diabetes.

Diabetes mellitus has become a major world health problem that has unenviable impacts on health of the people including quality of life (QOL) also and in which person’s physical and psychological state, social commitments and relationships and his interaction with the environment is affected. This shows that there is an urgent need for behavior change and considerable educational strategies for proper management and rehabilitation (Reddy, 2000). This research has identified and ranked the significant factors which affect the QOL in diabetic patients in India. The paper aims to discuss these issues.

In this paper, nine factors which affect the QOL in diabetic patients in India have been identified through review of the literature and evaluated by total interpretive structural modeling (TISM) approach, i.e. an extended version of ISM. In this approach, interpretations of the interrelationship among factors have been discussed. Therefore, TISM approach has been used to develop the model and the mutual interactions among these factors.

The results of the model and MICMAC analysis indicate that diet restriction, body pain and satisfaction with treatment are the top-level factors.

Identification of the factors that have a remarkable effect on the QOL in diabetic patients is very important so that the doctors and other healthcare professionals may handle these factors efficiently and proper rehabilitation can be provided to such patients.

This paper has used an application of the TISM approach to interpret the mutual relationship by using the tool of interpretive matrix and has developed a framework to calculate the drive and the dependence power of factors using MICMAC analysis. The issues related to QOL are extremely important, as they can strongly anticipate a person’s capability to govern his lifestyle with disease like diabetes mellitus and maintain good health in the long run. This shows the urgent requirement of an optimized model which can predict and interpret the relationships among these factors. In this research, the interrelationships among these factors have been developed and interpretations of these interactions have been given to develop a comprehensive model so that QOL of diabetic patients may be improved.