Category: Diabetes

Diabetes is a lifelong chronic illness that affects millions of Americans, African Americans in particular. In the years prior, a diagnosis could be devastating along with the health complications that follow. A person with diabetes would forever be tied to multiple prescription medications, insulin, syringes, and constant finger sticks to determine their blood sugar levels unless they would turn their health around for the better. Since then, there have been many advancements in diabetes-related to care for patients. New technologies have made the quality of life better for persons diagnosed with Type 1 and Type 2 diabetes.

The world as we know it has is being affected by many diseases due to poor health/family illnesses, known and unknown viruses, hypertension, obesity, sexually transmitted diseases, which are only a few diseases one can gain. However, there is one common disease that has not only America suffering but other countries as well are facing today. This disease is formally called diabetes, and by definition, Diabetes is a chronic disease that occurs when the pancreas is no longer able to make insulin, or when the body cannot make good use of the insulin it produces (International Diabetes Federation). This normally occurs when there are high levels of the “wrong foods” consumed. For instance, the famous McDonald’s, Burger King, Taco Bell, Wendy’s, and the majority of other fast-food restaurants offer extremely cheap meal deals like the “4 for 4” (Wendy’s) or “2 for $5 mix and match” (McDonald’s) to make it easy for Americans’ and others to be able to purchase a cheap meal but can be devastating to the body. Surprisingly, a select few restaurants that offer more “healthy’ food options are only really healthy as they say. A chain restaurant like Subway offers processed meats or artificial vegetables which are somewhere along the lines to be the same as eating fast foods. If you think about it, most of these fast-food restaurants are located where? Mainly in the poorer communities, where they know fast food can be afforded and comes out super quick. This brings problems all across the boards. Yes, it is offering the community an opportunity to feed their families by building these fast-food restaurants (especially if it is a big family), however, it is raising obesity in kids as well as adults, illnesses like hypertension, or the main illness which is diabetes. Diabetes is considered one of the main killers because if one doesn’t know that they have the illness, they can potentially kill themselves due to lack of knowledge and constant poor diet because of them being unaware of their health. The biggest question to answer, is which minority population is the most affected with diabetes, and what are some preventative measures the minorities can take to help resolve their complications with diabetes?

Williams defines ethnicity as “a complex multidimensional construct reflecting the confluence of biological factors and geographical origins, culture, economic, political and legal factors, as well as racism… The concepts of “race” and “ethnicity” play important roles in understanding disparities in health and health care (Spanakis & Golden, 2013). Depending on one’s racial status and ethnicity, race plays an imperative role when demonstrating the discrepancies that the health care system. This states that there is in fact problems that because of one’s race and/or ethnicity, they may or may not be treated for diabetes. It is somewhat stereotyping the races making diabetes a racial thing. Today, most diabetes cases are mostly found in African Americans, Hispanics, Asians, solely any race other than white. Because this is a known fact, it sorts of gave professionals the notion to pass the individuals by who have diabetes and seek medical attention. Most doctors don’t consider an African American or Hispanic patient a priority and would rather treat to a more “privileged” race, white people. This is an inequality that should be avoided, nor should any race be not be treated because of their race or ethnicity, or beliefs it is unfair and detrimental to the patient’s health.

In 2003, the Institute of Medicine released a landmark report titled “Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care,” providing evidence that racial and ethnic minorities are treated differently from whites in the U.S. health care system, resulting in poorer health for millions of Americans (Chow et al 2012). Being that the races are treated differently in the health care system, it shows us the disparities that the health care system directs towards a specific race. Based on the above research statement from the article, The Disparate Impact of Diabetes on Racial/Ethnic Minority Populations, basically says that those who are white are treated better or improved care than other races like Hispanic, black, Asian, Haitian, etc., which is completely unfair to those who seek the same or dire treatment than those of the white race. No race nor ethnicity should have to suffer because they are not the “privileged” race in order to seek medical treatment. Today, this is where not only America, but some other countries too, are failing to treat certain patients because of the extent of care that the patient may need in addition to the race of the person. Being that diabetes known diagnosis to treat, it is not a huge problem for the white races. According to the article, the authors also state that majority of the races who suffer from diabetes are African American (one of the highest races), Hispanic/ Latino, Asian Americans, and American Indians. The biggest issue is where the communities lack the opportunity to provide to the different races healthier food options to shop from like whole foods, fresh markets, more 24-hour fitness gyms to be able to travel to and possibly within walking distance. Diabetes can be controlled within each race if and only if there were to be changed in the community.

Abstract

Several health-oriented research makes use of machine learning strategies for the analysis, detection and the prediction of health dangers from specific attributes of patient health records. Diabetes is one amongst them, it is a frequent and extensive spread fitness troubles in India. Diabetes mellitus type 2 or type2 diabetes may additionally be a long-term disease it is considered via excessive insulin defiance, lack of insulin and excessive blood glucose levels. Several machine learning approaches such as supervised learning, clustering and regression etc., have been proposed. This paper surveys exceptional machine learning approaches used to manage fitness care information’s along with the end result summary. This survey explores the popular and high-quality computer learning and statistics mining strategies along with its pros and cons.

INTRODUCTION

Machine learning has a extremely good achievable for therapeutic development and healthcare, starting from discovery to analysis to deciding. There are quite a number ways of predicting the danger of diabetes in computing device gaining knowledge of however the accuracy of the prediction varies and is unreliable. The followings are the basic information’s about the diabetes and its simple motives and symptoms. Diabetes is a disorder at some stage in which your blood sugar , or blood glucose , stages are too high. Glucose comes from the foods you eat. Insulin can also be a hormone that helps the glucose gets into your cells to provide them energy. With kind 1 diabetes, your body doesn’t make insulin. With type two diabetes, your physique has a greater amount of glucose in the blood.

The range of folks with diabetes has risen from 108 million in 1980 to 422 million in 2014. The global prevalence of diabetes amongst adults over 18 years aged has risen from 4.7% in 1980 to eight .5% in 2014. In 2015 alone, an estimated 1.6 million deaths global have been at once attributed to diabetes. In addition, a diabetic affected person is at a greater hazard of growing cardiovascular disease, visual

Impairment and bear limb amputations, as compared to a non-diabetic person. Due to the extensive socio-economic burdens now not solely to the effected families however the local healthcare system as well, the early detection, intervention and prevention of diabetes has become a paramount world subject related to health.

Impaired glucose tolerance (IGT) determines the bizarre insulin response in the body, and is viewed one of the most vital hazard factors, both through the World Health Organization (WHO) and the American Diabetes Association (ADA), for detecting diabetes in its early stage, known as pre-diabetes. Studies have proven that only 50% of the instances that show off the IGT go on to strengthen diabetes in future. On the different hand, 40% diabetic topics do now not show any IGT in the preliminary screening.

It is crucial to are looking for out the easiest in shape algorithm that has larger accuracy, speedy and reminiscence utilization on prediction inside the case of Diabetes.

XISTING SYSTEM

The big dimension databases are protected in this manner as input. This manner resulted in information series complication.

The healthcare industry gives massive quantities of healthcare statistics which must be mined to determine hidden records for precious selection. Determining hidden patterns and relationships may frequently be very difficult and unreliable.

The fitness file is assessed and anticipated if they want the signs and symptoms of Diabetes danger and the usage of risk elements of disease. it is vital to are seeking for out the easiest match algorithm that has higher accuracy, speedy and memory utilization on prediction inside the case of Diabetes.

PROPOSED SYSTEM

As simply like the heart situation , the diabetes and its chance is assessed and envisioned with the aid of a variety of records processing strategies within the literature. we’ll additionally implement function decision and take away redundancy. The proposed system also promises high accuracy and consequently the capacity to cope with missing values and null values. It supports specific data.

METHODOLOGY

Firstly, the datasets were collected from Kaggle. Kaggle is platform the place businesses and researchers put up records and statisticians and data miners compete to supply the simplest fashions for predicting and describing the info. You can compete on many problems.

The features that were taken in the dataset were Pregnancy, Glucose, Blood Pressure, SkinThickness, Insulin, DiabetesPedigreeFunction, BMI, and Age. Since we cannot take all the features for training our model, we selected the main features that cause great impact that is Pregnancy, Glucose, Blood Pressure, and Age.

Feature selection is the technique of choosing the features manually or routinely that contributes to the model. Having all features may reduce the accuracy of the model. So feature selection is carried out to increase the accuracy of the model.

Glucose level, Insulin, Age, Pregnancies and Blood Pressure have increased impact on this model, mainly glucose stage and Insulin. Blood pressure has a terrible affect on prediction of diabetes, i.e. higher the blood pressure is correlated with a person now not being diabetic.

Feature Selection

We selected 10 features for our prediction model consisting of socio-demographic variables like age and ethnicity, and physiological factors that were either immediately measured or derived from the OGTT. These features have individually been used in preceding T2DM prediction studies. In our project, we have used Recursive Feature Elimination (RFE) technique for selecting vital features here. The Recursive Feature Elimination (RFE) works via recursively removing attributes and building a model on these attributes that remain. It makes use of the mannequin accuracy to perceive which attributes (and combination of attributes) contribute the most to predicting the goal attribute.

Feature resolution refers to strategies that select a subset of the most applicable features (columns) for a dataset. Fewer elements can permit desktop getting to know algorithms to run more successfully (less area or time complexity) and be more effective. Some desktop learning algorithms can be misled by beside the point enter features, ensuing in worse predictive performance.

Machine learning

In this study, we employed the linear SVM kernel with the aid of utilizing the Matlab’s svmtrain function. The coaching facts used to be first scaled to have a unit popular deviation. The mis- classification fee used to be configured by using putting the price of the box constraint parameter to a excessive price of 100, which would cause a stricter partitioning of the facts with appreciate to the classification labels. To predict the future danger of type-2 diabetes, we described a high quality category (occurrence of diabetes at the follow-up) and a bad type (healthy). As illustrated in Table I, the OGTT data used in this find out about is closely unbalanced. With 171 high quality category instances as in contrast to 1281 that of the terrible class, the measurement of category labels is unbalanced with the ratio of positive-to-negative situations of 1:8. To keep away from the problem of over becoming to the majority class all through the mastering segment of the technique, we under-sampled the majority classification (healthy) to the measurement of the minority classification (diabetic) by means of a randomly choosing equal wide variety of samples. During the prediction model generation, we employed 10-fold cross-validation framework in which 90 p.c of the coaching data, consisting of 360 samples was once used for coaching and the remaining 10 percent used to be used to take a look at the model. To validate the skilled models, we used a holdout data set with the equal unbalanced ratio of negative-to-positive instructions in the authentic data, i.e., eleven samples of the advantageous class, and 88 samples of the negative class. We commenced our experiments using one function at a time, and then greater quantity of features were incrementally added. This exercising assists in discovering any characteristic dependencies. In total, we performed 1,023 classification experiments. Each of these experiments was trained as a 10-fold cross-validation (CV) and, to decrease the impact of random choice of samples from the majority class, a hundred iterations were carried out for every experiment. Owing to the small sample measurement of the holdout dataset, this method ensures the independent reporting of the classifier performance.

Neural network works precisely the same way as the Genius works, with the aid of a remarks procedure called back-propagation. Here we would compare the output of the network with the favored output, and we use the difference between the outputs to alter the weights of the connections between the neurons, working from the output units via the hidden neurons to the enter neurons which is going backward.

Decision Tree

A decision tree is a tree like structure of decision and their possible consequences, it includes the resource cost and the utility. It is simple yet powerful learning method and a classifier model. It is a supervised machine learning algorithm. It provides tools for discovery of match, pattern and knowledge from data in dataset. Few important terms in decision tree structure are:

• ROOT NODE: It is the top most level of a tree and holds all the sub roots or nodes of a tree.
• SPLITTING: It is a method of dividing a node into two or more sub-nodes.
• DECISION NODE: When a sub-node splits into few more sub-nodes, then it is called decision node.
• LEAF/ TERMINAL NODE: It is the last node of a tree.
• PRUNING: The process of removing sub-nodes of a tree is called as pruning. You can say opposite process of splitting.
• BRANCH / SUB-TREE: A sub section of the whole tree is called branch or sub-tree
• PARENT AND CHILD NODE: A node divided into sub-nodes is called parent node of sub-nodes where as sub-nodes is a child of parent node. It has three main blocks, root node, decision node, terminal node.

Random forest

It is a supervised learning of machine learning language, which is used for classification problems and Regression problems. The logic behind this random forest algorithm is the bagging technique, this technique is used to create random sample features. The main difference between the methods, decision tree and the random forest algorithm is the actually the process of finding the root node and splitting the feature node which will run randomly. The Steps are given below:

• Load the data where it consists of “m” features representing the behavior of the dataset.
• The training algorithm of the random forest is called bootstrap algorithm or bagging technique to select n feature randomly from m features, i.e. to create the random samples, this model trains the new sample to out of bag sample(1/3rd of the data) used to determine the unbiased OOB error.
• Calculate the node d using best split. Split the node into two sub-nodes.
• Repeat the steps, to find n number of trees.
• Calculate the total number of votes of each tree for predicting the target. The highest voted class is the final prediction of the random forest.

RESULT

The aim of this paper is to explain a machine learning scheme that can identify healthy subjects that are at an increased risk of getting type-2 diabetes. For this, the data used here is a subset of the Kaggle website that includes the OGTT data of healthy subjects at baseline. To determine the performance of our pre-diction models, we use accuracy of different machine learning algorithm. During the training of this model, maximizes the identification rate of high-risk diabetes. Using the strategy described in the previous section, we show the performance results that are averaged over several iterations.

And during training, they trained ten prediction models with an increasing number of features. Each of the SVM classifiers was trained through a 10-fold cross-validation. The trained model was obtained by selecting the one that yielded the maximum accuracy averaged over several iterations. We will also be training the system with different machine learning algorithm, which would help in finding out the most accurate algorithm which would give the accurate prediction for the risk of diabetes.

The performance evaluation for the model of the classification techniques is done using different performance measure like accuracy using accuracy as the main. Our model focus on the four machine learning classification techniques such as support vector machine, Random forest, decision tree and Neural Network. We used constant dataset to perform the comparison.

Validation

The box plots for the validation is accuracy and therefore the specificity of the models that were trained to maximize the accuracy of the classifier. And an equivalent trends observed during the training were also seen within the validation phase. The mixture of the four features that yielded the simplest training performance also produced the very best median recall rate. Adding more number of features to the model resulted in slight improvement within the median accuracy. This validation performance of the models with maximized recall during the training.

CONCLUSION

Diabetes prediction models identify the risk of developing diabetes in an healthy population so that a timely population-based intervention could prevent future complications. During this process, we’ll be using the foremost accurate machine learning algorithm to construct a prediction model of future development of type-2 diabetes. We believe that prevention is better than the cure hence, we use this model to predict diabetes on the beforehand. During few possible extension of this study, the prediction models could also be applied on other similar datasets that include the OGTT measurements.

References

1. “Development of Disease Prediction Model Based on Ensemble Learning Approach for Diabetes and Hypertension” – (Norma Latif Fitriyani, Muhammad Syafurdin, Ganjar Alfian, and Jongtae Rhee).
2. “Decision tree support vector machine based on genetic algorithm for multi-class classification”- (Huanhuan Chen∗, Qiang Wang, and Yi Shen School of Astronautics, Harbin Institute of Technology, Harbin 150001, P. R. China).
3. “Usi Random Forest for Protein Fold Prediction Problem: An Empirical Study” Abdollah Dehzangi, Somnuk Phon-Amnuaisuk And Omid Dehzangi.
4. “Survey of different feature selection algorithms for diabetes mellitus prediction” (Prof.Rajesh Lomte, Sheetal Dagale, Sneha Bhosale, Shraddha Ghodake ).
5. “ “Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning” – ( Bum Ju Lee and Jong Yeol Kim).

Do you know a person who has type 2 diabetes? Perhaps at risk of cardiovascular disease? Maybe even some musculoskeletal conditions or a form of cancer? This person may have one of these illnesses and they may also suffer from obesity. Obesity has been defined by the National Institutes of Health as a Body Mass Index (BMI) of 30 and above, and it can critically influence people’s state of health. Obesity is the condition of being too heavy for one’s height so that a person’s health is affected. In other words, it means to be too overweight. Good morning everyone, I’m Abbi and I will be discussing how obesity is a major influence on people’s state of overall health. Firstly, I’ll start with the significant causes of obesity, following with chronic diseases that obesity can lead to, and finishing up with the effects of obesity on people’s mental health.

There are a variety of factors that stop people from avoiding obesity, and they are generally poor diet, environmental and other lifestyle choices. Obesity is diagnosed when your BMI is 30 or higher. In 2017-18, the Australian Bureau of Statistics’ National Health Survey showed that two thirds of adults in Australia, or 67%, were overweight or obese which is a 3.6% increase from 2015-16. 24.9% of children aged 5-17 were overweight or obese in 2017-18. Although there are genetic, behavioural, metabolic and hormonal influences on body weight, obesity occurs when you consume more calories than what you burn through exercise and normal daily activities. The imbalance between energy intake and energy expenditure are the two main factors that lead to being overweight and obese. The amount of food each person needs varies by age, gender, body size, and level of physical activity. Your body converts proteins, carbohydrates and fats in food into energy, and fat is the most concentrated source of energy. Energy expenditure is the amount of energy, or calories a person uses daily to complete normal activities and physical activity. Your total daily energy expenditure is the total amount of calories you’ve burned throughout the day. The human body uses energy in three ways: basal metabolism (energy used to maintain vital bodily processes such as breathing or circulating blood), thermic processes (energy taken to absorb and digest food), and physical activity (energy used for movement).

Being overweight or obese can inhibit the ability to control or prevent several chronic diseases that are linked to obesity. These include heart disease and stroke, high blood pressure, diabetes, osteoarthritis, sleep apnoea, and certain cancers. These medical issues can be caused by obesity and it deteriorates health and can even lead to death. Poor lifestyle choices such as smoking, overuse of alcohol, poor diet, and a lack of physical activity are the root causes for the development of preventable chronic diseases. A healthy diet significantly contributes to a healthy weight, quality of life and wellbeing, and prevent the risk of chronic disease and premature death. The Australian Dietary Guidelines provide recommendations to address the dietary risks that subsidise to obesity. The Guidelines have grouped foods together which share similar nutrients and we know these as the five core food groups. These are: grains and cereals, vegetables, fruit, dairy, and lean meats. Data from a Victorian Health Survey in 2014 shows that only 4.4% of adults met both the fruit and vegetable dietary guidelines. While dietary guidelines in Australia exist, Australians’ diets have a high intake of discretionary foods, which are often high in fats, sugars, salt and alcohol, along with insufficient intake of foods that contribute to health and wellbeing. These are significant risk factors for chronic disease.

Finally, obesity is known to trigger several psychological disorders such as depression, eating disorders, distorted body image, bipolar disease, schizophrenia, and low self-esteem. European studies show that children with obesity face a 63% higher chance of getting bullied. When children and young adults get victimised for their weight it can be a stigma to feelings of shame and anxiety, which can lead to depression, low self-esteem, poor body image and even suicide. Research over the years has shown that mental health and obesity are linked, and some are considering that obesity is a mental health illness and suggests people with depression develop metabolic illnesses. People may consume large amounts of “comfort foods” which are high in sugars, sodium, fats and calories because they are anxious, lonely or suffering from low self-esteem.

With a growing population and the high availability of cheap unhealthy foods along with the thousands of advertisements almost everywhere you go, watch on the tv or hear on the radio, it is easy to say young children and the rest of today’s society have a lack of nutritional education. Nutrition is an important factor of healthy daily lives however; children and adults are not taught on how to eat the right foods in the right proportions. Nutrition education is extremely important for children as it forms them to make the right decisions about what the consume when they reach their teenage years and adulthood.

Sugar has been proven to be able cause many diseases. It has been scientifically shown by science, that drinks sweetened with sugar can cause an increase in visceral fat and can also cause a raise in blood pressure. Consuming a lot of sugar has also been proven to trigger the liver to discard dangerous fats into the walls of arteries, which can clog them up, slowing down the travel of the blood and can cause disease like heart disease and symptoms like fatigue.

The body requires energy to function and gets most of it from sugars found in foods. The body will use sugars and exert it for exercises and movements. The leftover sugars are converted into fats (or lipids) and are stored in . The body turns sugars into of fats by a procedure called lipogenesis. Lipogenesis is a process in the liver in which glucose is converted into triglycerides, a type of fat. After lipogenesis, the fat cells are grouped with other fat cells to create adipose tissue and are stored until it is needed. Adipose tissue is also used to insulate the body. When the body uses the fats, they are absorbed into the blood and travel to where the energy is needed. As fats flow through the bloodstream, they begin to clog up the walls of arteries, which can slow down the blood. Blood-pressure is also a common way for sugars to cause blood pressure. “Researchers pooled findings from six studies that included a total of more than 240,000 people. They found a 12% higher risk of high blood pressure among people who drank one or more sugary drinks daily compared with those who drank none.” (Sugary drinks seem to raise blood pressure, 2015). High blood pressure can damage the body due to the pressure of blood having to pass through arteries that have a build-up of fat, which means that the heart won’t get enough blood, which can cause heart-disease.

The body needs glucose inorder to create energy for the cells. It does that through a process called cellular respiration. The formula for cellular respiration is glucose + oxygen → carbon dioxide + water and energy. Inorder to keep the sugar levels your body needs, the pancreas releases insulin. If the body releases too much insulin, you can get a resistance. If your sugar levels are higher than you need, insulin will help store the sugar in the liver so that if it is too low, it can be used. Low sugar levels can cause a disease called hypoglycaemia, which, due to a lack of energy from sugar, can show symptoms like unconsciousness, seizures and can make the body feel weak. High sugar levels can a cause a disease called hyperglycemia, which can cause symptoms like fatigue, headache and thirst/hunger. High sugar levels means the body has to release large amounts of insulin, which can cause type 2 diabetes.

The school provides a few healthy options for food, however the rest of it is not healthy. A few of these unhealthy examples include, CHILL Chocolate Milk, Golden Gaytime ice-cream and Lipton Iced Tea. CHILL contains about 22.2g of sugar per serving. Golden Gaytime contains about 17g of sugar per serving. Iced Tea contains about 26.4 g of sugar per serving. Instead of these 3 unhealthy items, the school canteen could provide students with no-sugar Kombucha, coconut water and Waterfords Lite & Fruity Natural Mineral Water.

Sugar has been proven in many ways to damage the human body and cause many types of disease. High blood pressure and heart disease are caused by sugars that are converted into lipids and dumped into the wall of arteries and slow down blood flow. Sugars also cause diabetes when the body consumes too much sugar, which releases enough insulin from the liver for the body to gain a resistance to insulin.

Bibliography

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2. Hess-Fischl, A. (2018, 07 09). Hyperglycemia: When Your Blood Glucose Level Goes Too High. Retrieved from endocrineweb: https://www.endocrineweb.com/conditions/hyperglycemia/hyperglycemia-when-your-blood-glucose-level-goes-too-high
3. Hess-Fischl, A. (2019, 05 28). What Is Insulin. Retrieved from endocrineweb: https://www.endocrineweb.com/conditions/type-1-diabetes/what-insulin
4. How Does Sugar Turn Into Fat? (n.d.). Retrieved from DietDoc: https://www.dietdoc.com/weight-loss-science/how-does-sugar-turn-into-fat/
5. How Sugar Converts to Fat. (2014, July 16). Retrieved from Health, University of Utah: https://healthcare.utah.edu/the-scope/shows.php?shows=0_7frg4jjd
6. Hughes, L. (n.d.). How Does Too Much Sugar Affect Your Body? Retrieved from WebMD: https://www.webmd.com/diabetes/features/how-sugar-affects-your-body
7. Low Blood Glucose (Hypoglycemia). (2016, August Martha Funnell). Retrieved from National Institute of Diabetes and Digestive and Kidney Diseases: https://www.niddk.nih.gov/health-information/diabetes/overview/preventing-problems/low-blood-glucose-hypoglycemia
8. Permanete, K. (2019, 03 01). How our bodies turn food into energy. Retrieved from Kaiser Permanete: https://wa.kaiserpermanente.org/healthAndWellness?item=%2Fcommon%2FhealthAndWellness%2Fconditions%2Fdiabetes%2FfoodProcess.html
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What is diabetes? It’s a disease that produces the hormone insulin and results in abnormal metabolism of carbohydrates it elevates levels of glucose inside urine and blood. It also affects how your body uses glucose. If your sugar is too low or too high you have a serious emergency, you have to balance your sugar in order to have the right amount. There are four different types of diabetes as Type 2 diabetes, Type 1 diabetes, Prediabetes, and Gestational Diabetes, they all have different effects when it comes to diabetes. When you have Type 2 diabetes your body has tons of trouble making insulin and insulin is very important for the body.

Type 1 diabetes is also Called juvenile diabetes it is a typical condition where the pancreas produces not too much insulin or no insulin at all. Impaired glucose tolerance which is Prediabetes usually adults have Prediabetes, it contains high blood sugar but not as high as type 2 diabetes within ten years it could probably become type 2 diabetes. Gestational diabetes is usually what pregnant women have, it’s high blood sugar that affects pregnant women. Usually, people who develop gestational diabetes will eventually have Type 2 diabetes. Diabetes is actually the number one cause of death. Whether you know it or not but Type 1 occurs at any age group, and yet it’s usually the worst one to have. Its many foods that cause diabetes, processed meat and red meat are usually what cause type 2 diabetes because of the high levels of sodium. There are also risk factors of diabetes such as being overweight, having a sedentary lifestyle, intake of high alcohol, and carbohydrate diet. Diabetes is the most common disease that people have, you hear it everywhere and nine times out of ten a family member of yours just might have it. It’s not very easy fighting diabetes with being sick all the time and close to death is very hard it is pretty much a struggle. The main reason behind diabetes is insulin, but what is insulin? And why do we need it so badly? Insulin is a hormone made by the pancreas, insulin helps keeps your blood sugar level at the right amount, not too high or not too low of course.

Insulin also provides cells the energy to function, so basically, you need insulin to stay alive. Some people may think they are in good health at times but you can feel that way and also have a chance of having diabetes. Insulin also breakdown fats for energy, the balance of insulin regulates blood sugar and another process in our body. If you have insulin problems the immune system attacks the islets, islets somewhat produce the insulin. There are also many types of insulin such as Long-acting insulin, intermediate-acting insulin, and fast-acting insulin. The health status of the people and poor indicators of health in the region, the government launched the health care reforms in 2001 to help alleviate the growing problem in the health sector. However, the government of Pakistan spends about 0.8% of GDP on health care, which is lower than some neighboring countries such as Bangladesh (1.2%) and Sri Lanka (1.4%). Although the government provides funding for diabetes as part of the general health system budget, diabetes itself receives an insignificant share of the fund. Additionally, specific funding through private and international collaborators is very limited. Moreover, there is no framework for diabetes monitoring and surveillance.

Self-management approach in a global context. The current literature reveals that diabetes self-management is the cornerstone of diabetes care. Several studies have reported that diabetes self-management is associated with improved diabetes knowledge, self-management behaviors, and clinical outcomes. However, in a meta-analysis of diabetes self-management programs, Norris et al. reported sharp declines in benefits within one month post-intervention suggesting that self-management interventions alone do not enable individuals to maintain behavior changes. Therefore, it is evident that the behavior changes after the implementation of self-management programs require the co-existence of several factors. They suggested that quality clinical care and self-management are compatible and dependent on each other. Therefore, in the absence of sound care, an individual’s efforts may be misdirected, and expert clinical care will fall far short of its potential.

In diabetes management, patients may fail to use prescribed medications to control blood sugar or to implement the management plans. Diabetes is a disease in which the body is unable to properly use and store glucose (a form of sugar). Glucose backs up in the bloodstream — causing one’s blood glucose (sometimes referred to as blood sugar) to rise too high. This form of diabetes usually develops in children or young adults but can occur at any age. Guidelines for preventing or lowering your risk of developing type 2 diabetes are also appropriate if you currently have a diabetes diagnosis. This course covered the annual review for people with diabetes. You have seen that even if someone feels they are in good health, they may still have risk factors that could increase the chances of getting diabetes-related complications. It is important to create a plan, which is agreed between the person with diabetes and the health professional, to show what actions need to be taken to reduce risk factors or maintain low risk. I have learned and research things such as diabetes being very risky.

What is diabetes?

Diabetes is a metabolic disease that is characterized by increased blood sugar or hyperglycemia. It can occur due to derangements in insulin secretion, action or both. This increased blood sugar state can affect different organ systems which include blood vessels, eyes, heart, nerves, kidneys, and foot. Long standing diabetes is known to cause damage, dysfunction, and failure of these organs.

How diabetes affects the foot?

Diabetes can cause micro vascular and macro vascular complications. In the foot diabetes can lead to diabetic neuropathy and peripheral vascular disease. About 10% of patients develop foot ulcers due to these complications. Uncontrolled diabetes and chronically raised sugar levels damage the ability to sense pain and temperature leading to diabetic neuropathy. In 90% of the patients distal symmetrical polyneuropathy (DSPN) is the commonest form of sensory diabetic neuropathy (Tesfaye, Boulton and Dickenson, 2013). Peripheral vascular disease affects the blood circulation to the extremities and because of low blood flow the infection risks are greater. This can lead to gangrene and ulceration. Due to severe ischemia secondary to these mechanisms patients can be completely asymptomatic. (Figure 2) This highlights the importance of regular foot screening in diabetics.

Global burden of diabetes

The International Diabetes Federation estimated that 425 million people in the world are affected by diabetes of which 46% are undiagnosed. By the year 2045 this figure is expected to rise to 629 million.

What is screening?

According to WHO “Screening is defined as the presumptive identification of unrecognised disease in an apparently healthy, asymptomatic population by means of tests, examinations or other procedures that can be applied rapidly and easily to the target population.”

The lifetime risk of a person with diabetes developing a foot ulcer could be as high as 25% (Singh, 2005). Poor diabetic control and management of diabetic foot complications result in amputation. (New et al., 1998) says that the relative risk of amputation associated with all types of diabetes is 13 times that of non-diabetics. Thus, foot screening is mandatory in diabetics and should be done at regular intervals.

Goals of screening:

• Prevention and or early detection, of diabetic foot complications
• Appropriate treatment and management
• Reduce progression to amputation

When to screen? (NICE) (2015), (SIGN) (2017)

• At diagnosis
• Annually there after
• If the patients notice any new/significant change

How to screen?

• Validated foot screening questionnaire
• Inspection
• Sensory testing
• Palpation of peripheral pulses
• Check for foot deformities and callus
• Previous foot ulcerations/ Gangrene

Screening should include conventional clinical examination, history, agreement on treatment regimen/ risk stratification, education on diabetic foot and rapid referral to appropriate specialist if needed. (NICE) (2015), (SIGN) (2017)

History

• Detailed personal and diabetic history (age, gender, ethnicity, duration, medication, blood sugar control, symptoms of hyperglycemia, hypoglycaemia, ischemia and neuropathy)
• Previous and current foot complications (repetitive minor trauma, use of over the counter medications)
• Detailed medical and surgical history (Rheumatoid arthritis, Renal disease, Cardiovascular disease, any surgeries including amputation, peripheral vascular disease)
• Social history (Managing daily activities, physical exercise, smoking, alcoholism)

Examination:

• Skin over the foot (Colour, pain, abrasion, ulceration)
• Neuropathy (using graduated tuning fork, thermal discrimination devices, 10g monofilaments, or vibration perception thresholds (Young et al., 1994) (Abbott et al., 1998)
• Peripheral vascular disease (palpation of peripheral pulses preferred for screening, ankle brachial pressure index can be falsely high in patients with elevated systolic pressures)
• Foot deformities (hallux valgus, hallux rigidus and hammer toes, claw toes, ankle equinus, high arch and calluses)
• Appropriate foot wear

Education

Appropriate education about the disease and complications has yielded both short term and long-term improvement amidst the patients (Valk, Kriegsman and Assendelft, 2002).

• Considering factors such as ethnicity and age when educating patients are important.
• Self-care and monitoring, good foot hygiene, nail care, self-examination and use of moisturisers
• Explain the danger signs such as blood-stained callous, skin injuries and infections
• Dangers of neglect should also be communicated to the patient
• Foot wear advice

Appropriate referral

• Supervision of a multidisciplinary diabetic foot care team (specialist podiatrists, orthotist, nurses with training in diabetic wound care, diabetes physicians, vascular surgeons, interventional radiologists and microbiologists.)
• Onward referrals to, and supervision of treatment by necessary specialists

For screening programmes to run effectively access to specialist services must be rapid, and there should be good communication between the primary and secondary care providers

Conclusion

The global burden of diabetes is on the rise, this is mostly attributed to the increasing population, life expectancy and modification of lifestyle including urbanisation. It is thus imperative to introduce a uniform screening and management guideline to prevent diabetic complications (Formosa, Gatt and Chockalingam, 2016).

The famous Scottish poet Thomas Campbell once wrote, “Coming events cast their shadows before.” Proper screening and patient education with prompt and appropriate referral can go a long way in minimising the impact of diabetic foot complications.

BIBLIOGRAPHY

1. SKYLER, J.S., BAKRIS, G.L., BONIFACIO, E., DARSOW, T., ECKEL, R.H., GROOP, L., GROOP, P., HANDELSMAN, Y., INSEL, R.A., MATHIEU, C., MCELVAINE, A.T., PALMER, J.P., PUGLIESE, A., SCHATZ, D.A., SOSENKO, J.M., WILDING, J.P.H. & RATNER, R.E., 2017. Differentiation of Diabetes by Pathophysiology, Natural History, and Prognosis. Diabetes. 66(2), pp.241-255. Available from: http://dx.doi.org/10.2337/db16-0806.
2. TESFAYE, S., BOULTON, A.J.M. & DICKENSON, A.H., 2013. Mechanisms and Management of Diabetic Painful Distal Symmetrical Polyneuropathy. Diabetes Care. 36(9), pp.2456-2465. Available from: 10.2337/dc12-1964.
3. ARMSTRONG, D.G., BOULTON, A.J.M. & BUS, S.A., 2017. Diabetic Foot Ulcers and Their Recurrence. The New England Journal of Medicine. 376(24), pp.2367-2375. Available from: http://dx.doi.org/10.1056/NEJMra1615439
4. INTERNATIONAL DIABETES FEDERATION. DIABETES ATLAS EIGHTH EDITION 2017
5. WORLD HEALTH ORGANISATION
6. SINGH, N., ARMSTRONG, D.G. & LIPSKY, B.A., 2005. Preventing foot ulcers in patients with diabetes. Jama. 293(2), pp.217-228. Available from: https://search.proquest.com/docview/67362230?accountid=15977
7. NEW, J., MCDOWELL, D., BURNS, E. & YOUNG, R.,1998. Problem of amputations in patients with newly diagnosed diabetes mellitus. Diabetic Medicine. 15(9), pp.760-764.
8. NATIONAL INSTITUTE FOR HEALTH AND CLINICAL EXCELLENCE (NICE), Diabetic foot problems, Patient Management of Diabetic Foot Problems London: NICE, 2015
9. SCOTTISH INTERCOLLEGIATE GUIDELINES NETWORK 2017, SIGN 116: Management of Diabetes, Scottish Intercollegiate Guidelines Network, Edinburgh.
10. YOUNG, M., BREDDY, J., VEVES, A. & BOULTON, A., 1994. The Prediction of Diabetic Neuropathic Foot Ulceration Using Vibration Perception Thresholds: A prospective study. Diabetes Care. 17(6), pp.557-560.
11. ABBOTT, C., VILEIKYTE, L., WILLIAMSON, S., CARRINGTON, A. & BOULTON, A., 1998. Multicentre Study of the Incidence of and Predictive Risk Factors for Diabetic Neuropathic Foot Ulceration. Diabetes Care. 21(7), pp.1071-1075.
12. SCOTTISH DIABETIC FOOT ACTION GROUP (SDFAG) 2016
13. VALK, G., KRIEGSMAN, D. & ASSENDELFT, W., 2002. Patient education for preventing diabetic foot ulceration. Endocrinology and Metabolism Clinics of North America. 31(3), pp.633-658.
14. FORMOSA, C., GATT, A. & CHOCKALINGAM, N., 2016. A Critical Evaluation of Existing Diabetic Foot Screening Guidelines. The Review of Diabetic Studies. 13(2-3), pp.158-186.

When people talk about epidemics, there are thousands of different diseases in the world and depending on the danger levels or the short or long term. One of them is diabetes disease. Diabetes is a long-lasting disease that can influence at any age. Family can be one reason for an individual to have diabetes. Not just adults have diabetes even kids currently are getting diabetes because of eating unfortunate nourishments that contain a great deal of fat, sugars and not exercising or moderating the food intake that leads them to be overweight, which makes them have diabetes. This sickness is the 6th leading reason for death in the United States. After all, Diabetes Mellitus is a gathering of metabolic issues portrayed by deficient insulin secretion by the pancreas or cell decimation prompting an insulin insufficiency. Despite the fact that type 1 Diabetes Mellitus is as yet the fundamental type of sickness in youngsters, all things considered, type 2 Diabetes Mellitus will win in youthful patients soon. Diabetes also might come from your family generation, lack of exercise, overweight, diabetes can be subcategorized into sort I and type II. Type I is Diabetes Mellitus and type II is Gestational Diabetes. Type 2 diabetes mellitus has just been displayed in youngsters from various nations. Why do people need to take this problem seriously that is because it can affect your kidney damage, circulatory system, and integumentary system which is your skin the largest organ of your body, central nervous system, and reproductive system. These conditions also can incorporate cardiovascular illness, renal ailment, loss of vision.

Here are some advantages (pros) if you consciously protect and care about your health from Diabetes or help you’re healthy to become healthier. Controlling unhealthy life can make your life better because if you don’t control you can die easily. The average life expectancy for people with diabetes is shorter than people without it. You can save a lot of money if you control your lifestyle and live healthily, so there will be no bad diseases growing in your body and if so just don’t have to spend money and waste on it. For example, my father, and some of my aunts, uncles also had diabetes before. From what has happened I know it took a lot of money and a lot of time to get over it. My father still has high sugar blood and I don’t think he can get rid of it but he’s trying to improve and make his meals healthier. He also exercises, eats less, and tries to control not eating bad food. It is difficult to control diabetes since it manages the creation of insulin from the pancreas and how it directs to the liver to pass sugars in the circulation system. My father explains that when an organ doesn’t work the procedure is delayed down, and on certain occasions, one may not be capable produce much insulin to control the glucose levels. It can avoid damage heart, avoid, eye damage and avoid neurological complications. Diabetes may occur as a result of another disease or condition like cystic fibrosis, hemochromatosis, or chronic pancreatitis, just to name a few, there are even more types of diabetes.

There are also some people who disagree that diabetes does not affect your life. People think that they don’t have to control themself from anything because they think it is not important. They never take it seriously to care about their health and their lifestyle. They think it is right that they can eat whatever they wanted to and not doing any exercise or even try to eat less, not have a diet plan. People do it but they never think about the result after it, that’s why so many people were dying because they are not take it as important as it is. Facts that many people don’t even know that their blood sugar is high and that’s one of the reasons why over the world the diabetes cases are still increasing but not as quickly as last few years. This type of people mostly was in type II which is Gestational Diabetes is a silent, invisible disease that creeps up on you unawares. You look and feel the same without realizing that you’re on the road to diabetes. Some people said it is not dangerous compare to cancer so they don’t care.

There are some cons about why people should care about their health more than that you can follow. You can no longer eat many unhealthy foods; for example, fast food, chocolate, cheese, noodle, etc. Eating big meals at one time makes your body can’t digest and it will affect your stomach and your body. No running, no walking, not go to the gym or don’t do any exercise, activity will make your body become extremely lazy and can gain weight easily. Stress is a feeling of facing threats that are beyond people’s power to control. Stressing giving hormones to the human body such as cortisol will affect your body insulin resistance and raise your blood pressure to pump more blood.

From what my family has and outside the world, I believed that it is very important to care about what you eat every day and check your health daily. Everyone should take diabetes seriously as any cancer or any disease that you affect bad unhealthy things to their body.

A systematic literature search in Nelson and CINAHL database for primary studies published in English were used to obtained articles ensuring reliability, quality and relevance (Aveyard, 2010) reason why Google and Wikipedia were not used. Sequence of key words such as: diabetes type 2, socioeconomic class/group/position, risk factors in UK, type 2 diabetes quality of care in the UK, type 2 diabetes difference in care management, inequalities in UK type 2 diabetes treatments, differences in type 2 diabetes management globally, deprivations in type 2 diabetes in articles title (see appendix 1). Among the database mentioned Nelson was mainly used as it provided many articles which were relevant to the topic. The National Institute for Health and Care Excellence (NICE) guidelines for type 2 diabetes updated in 2017 was looked at as well as publications from the Department of Health (DOH), WHO, Diabetes UK, Government website (Gov.UK), Nurses and Midwifery Council (NMC), International Diabetes Federation (IDF) were used as well as a seminal piece from Newcastle University research.

The timeframe of this articles was restricted to the last 10 years to enable comparability between all the studies. As a result, only articles published between 2008 and 2018 were selected. This generated a great number of articles and as a result a suitable inclusions and exclusion criteria were adopted to narrow findings (see appendix 2). A range of peer-reviewed literature including both qualitative and quantitative were looked at. Qualitative research aims to understand, interpret the thought and reasons of people concerning a subject (Streubert and Rinaldi, 2011). This method adopts a systematic and explicit method of analysis which is reproducible. This research method may delineate preliminary questions which quantitative research can then address (Aveyard, 2014). On the other hand, a quantitative research method quantifies the problem developing a numerical data which can also generate statistics generalising it findings from a vast sample population (Streubert and Rinaldi, 2011). On first trial many of the key words were returning nothing useful therefore, they were disregarded and some words were altered to retain appropriate information. Hits were high with some keywords therefore the filters had a significant role in narrowing it down leading to a manageable number of articles to choose from. An abstract review was adopted to choose final articles relevant to the topic. Through this method 17 articles were chosen for the themes. Critical Appraisal Skills Programme (CASP) was adapted to critiques these articles. CASP is a NHS supported tool based on the importance of systematic review in evidence based practice, result interpretation and features of a high-quality review but also help to locate effectively systematic reviews. Through systematic review and critique of this literature the following themes were identified: socioeconomic inequalities, mortality, lifestyle.

SOCIOECONOMIC POSITION

Studies mentioned in the literature suggest there is a link between socioeconomic position and type 2 diabetes. According to Read et al., (2016) strong evidence of this was found in the Scottish diabetes survey produced by the Index of Multiple Deprivation which point out massive type 2 diabetes inequality prevalence as 77% of the people living in low quintile were more at risk compared to the 23% with a higher socioeconomic position living in non-deprived areas. Highlighting, that between 2004 and 2013 there were 180,290 people in Scotland diagnose type 2 diabetes which mostly involved young adult. Data collected from 350 General practices around the UK outlined doctor diagnose type 2 diabetes in men living in poor quintile was approximately 1.5 times higher compared to those living in privileged areas whilst the women were twice higher compared to people living in non-deprived areas (Read et al., 2016). Interestingly, further analysis proved that mortality prevalence of type 2 diabetes linked with socioeconomic position and age were 1.38 higher in men and 1.49 higher in women living in deprived areas. This proves young people living in more deprived areas have a high risk of developing type 2 diabetes leading to major health complications and premature death (Read et al., 2016). The study conducted by Read et al., (2016) presents two significant strengths. Firstly, this study was based on a large sample size as it used a big population register, which included 99% of type 2 diagnosis in Scotland and used national death registration data to analyse mortality trends. However, it could be argued this study cannot be generalised to all UK population, as ethnicity and food culture ware not considered. On the other hand, data collection accuracy could be argued as this was done routinely increasing the possibility that people diagnose with type 1 diabetes may have misclassified as type 2 diabetes and added to the figures.

Socioeconomic position is strongly linked with type 2 diabetes even when factors such as lifestyle and obesity are considered. An important finding was the study of the African American women conducted by Supriya Krishnan et al., (2010). This study examined the neighbourhoods in which African Americans women live based on their socioeconomic status and the prevalence of developing type 2 diabetes. Data was collected through a biennial follow up structured questionnaire sent by email to the 43.382 participants. This study started in in 1995 and lasted for twelve years and participants were aged between 30 to 69 years. And in other to assess neighbourhood socioeconomic status the US census block were use. Each census block containing approximately 1.500 people. There was a significant positive correlation between income and education in relation to indicators of socioeconomic position as well as individual’s neighbourhood. Comparatively, the study found out people living in deprived neighbourhood had 20 to 25% higher risk of developing type 2 diabetes (Supriya Krishnan et al., 2010). Interestingly, they also point out the relation between neighbour socioeconomic position with type 2 diabetes prevalence was also present within the African American women who had better education and higher income. An advantage of this study is the large sample size and the fact that it focuses on a specific sample type: African American women. However, one limitation of this study is the reliability of the data as the questionnaires are completed electronically and participants self reported, this could present bias (Aveyard, 2014).

It is widely recognised individuals with higher socioeconomic position have a better health compared to individuals with low socioeconomic status who present in general poor self-rated health (Read et al., 2016). On the other hand, the evidence from Kivimaki et al., (2015) study aimed to find how long working hours of manual labour associated with low socioeconomic position is a risk of developing type 2 diabetes. The study through meta-analysis included 222,120 people of both gender from Europe, United State of America (US), Australia and Japan. The most interesting founding was that there is a higher incidence of type 2 diabetes in low socioeconomic population who work long hours considering other factors as physical activity, age, obesity and gender. As people with manual labour job that worked 55 hours a week due to their low socioeconomic position increased the risk of type 2 diabetes of 30% compared to those who work 35 to 45 hours per week. However, it could be argued the study conducted by Kivimäki et al., (2015) presented some limitation. Even though the meta analysis data used covered Australia, USA, Europe and Japan not all the research was population based, therefore this finding cannot be generalising to all countries (Aveyard, 2014). Another limitation is the fact that working hours was measured based on a single assessment and there was no specific definition of what long hours means as this might differ in the countries mention above. However, and advantage off this study was large sample size (Aveyard, 2014).

All studies mentioned above highlight socioeconomic inequalities as a risk factor of type 2 diabetes as treatment management, awareness of this disease, it complications as well as accessibility to health allied support services may differ base on patients’ groups neighbourhood or income. Meaning some health services are way below the NICE standards as there’s no devoted service structure in place (NICE, 2017). These studies all have similar opinions and obtained significant result to clearly state socioeconomic deprivation raise inequalities among different patient groups.

MORTALITY

There is a large research on mortality within the field of type 2 diabetes and socioeconomic positions emerging as an important feature in the literature review. Else-Marie Dalsgaard et al., (2015) through a population base study examined 2.330.2006 participants aged 40 to 69 years who had no past medical histor of type 2 diabetes. The study lasted for 11 years. This study estimated mortality rate ratio and age standardised mortality rate of type 2 diabetes whilst taking into account participant home income, their neigbourhood base on socioeconomic status and their level of education. During this study 195.661 participant died and 19.959 of these was diagnosed with type 2 diabetes. The study conducted by Dalsgaard et al., (2015) suprisingly find out both socioeconomic position as well as type 2 diabetes were strongly connected to the mortality cases. There was a significant difference between higher income quintile individuals who had no type 2 diabetes the mortality rate was 2.8 higher for people with type 2 diabetes living in deprived quintile and type 2 diabetes itself increased mortality rate of 2.0. However, this study conducted by Dalsgaard et al., (2015) have some limitations as factors such as smoking status, bodi max index, physical activities, and clinical conditions were not taking into accont. On the other hand, data from this study included the Danish registers enabling reliable data colection which can be consedered as strenght (Aveyard, 2014).

Mortality is of key concern in the literature as outlined in the previous study. Walker, J.J. et al., (2011) similarly conducted a study to identify mortality rate in type 2 diabetes individuals. The Scotish eletronic database was used to obtain mortality records among people aged 35 to 84 years between 2001 and 2007. Quintiles 1 and quintiles 5 were adopted to measure low socioeconomic deprived neighbourhoods and the high socioeconomic priviladge areas. To measure the incidence of mortality rate and estimate it associated risks among those diagnose with type 2 diabetes and those who don’t have this condition a poison regression was used and gender, age, socioeconomic position and the duration of type 2 diabetes were taken into account as variable factors. The study included 210.994 participant of which 33.842 deaths and results showed mortality significantly increased increased more for men compared to women as socioeconomic deprivation and age increased. Strenghts of Walker, J.J. et al., (2011) study, a part from the large sample size is the use of a population based eletronic database which includes data from five of the thousand primary care practices in Scotland. However, the area base quintiles adopted to measure socioeconomic position instead of an individual based measure can be seen as a limitation (Aveyard, 2014).

On the other hand, Smith, B.T. et al., (2011) examined the level of cumulative life course of socioeconomic position linked with type 2 diabetes prevalence in young adults vary by gender. And also to analised if low socioeconomic position increase type 2 diabetes incidents during adulthood or childhood. Data was collected through 1.893 male and female from Framingham Offspring study who have been folowed up for 30 years. Roughtly every four years partecipant were asked to complete a standardised questionaire and undertake a physical examination, a doctor’s check to keep medical hystory up to date. Both men and women cumulative socioeconomic position was straightly linked with smoking, body max index, hight and higher consumption of alcohol. Findings of this study revealed theres an

Chronic complications of Diabetes mellitus (DM), which are present in as many as 50% of the diabetic patients at the time of diagnosis, are a major burden for both the patients and the healthcare system at large. It is estimated that, more than two-third of healthcare expenditure related to diabetes is mainly attributed to chronic complications of the disease (Hahr & Molitch 2015). This problem is further aggravated by poor lifestyle, aging population, and urbanization makes the situation even more challenging. Chronic kidney diseases (CKD) affects nearly 40% of individuals with diabetes in the UK, making it one of the most common complications related to the diseases (Berns et al. 2015). The risk of renal failure is 25% high in a diabetic patient than the non-diabetic individuals. As such, individuals with renal failure and diabetes presents a special risk group as they have high morbidity and mortality, and are at a higher risk of hypoglycaemia than diabetic patients with normal renal functions (Hahr & Molitch 2015). Therefore, physicians need to formulate a comprehensive management plan to counter complications presented by renal failure in diabetic patients.

Advanced renal disease among diabetic patients is a life threatening condition low survival rates and numerous complications. The kidneys are no longer able to support a reasonable health state, and immediate dialysis or kidney transplantation is needed. However, this not achieved easily as compared to non-diabetic patients because of the high susceptibility to infections, problems with vascular access, fool ulcer ad hemodynamic instability during haemodialysis (HD). Nevertheless, comparing kidney transportation and dialysis(both peritoneal and haemodialysis), the former, remains to be one of the most preferred therapy for diabetic patients with end state renal disease (ESRD) as it is associated with high survival rates and high quality life compared to the latter.

Diabetes and ERSD synergistically boosts the risk of cardiovascular disease (CVD). Individuals with diabetic nephropathy are highly predisposed to CVD compared to diabetic patient with no kidney disease. Well document research shows that patients with significantly reduced kidney function are not only subjected to the Framingham risk factors, but also a host of renal related factors, which further accelerate the advancement of cardiovascular disease (Wang 2011). Another study shows that cardiovascular disease-related mortality is higher for patients with diabetic nephropathy than individuals without diabetes (Chang et al 2014). Understanding the different risk factors of cardiovascular in these group of patient is important in its management. There is a strong evidence that demonstrate a strong linear relationship between high blood pressure and CVD. As such, maintaining the blood pressure within the nominal limits will help in reducing the risk of having CVD. Optimum blood pressure can be reducing through adjusting lifestyle such living a active life, avoiding smoking or excessive use of alcohol. Other pharmacological treatments can be applied to treat hypertension.

Oral agents, particularly insulin are regarded as the best choice to improve glycaemic control in patients with renal failure. However, specific information regarding dose adjustments and differences in insulin profiles in this group of patients is limited because of the few studies carried out in individuals with significant renal insufficiency. Further,there is no consensus about the choice of various preparation of insulin in patients with CKD. However, based on clinical practice, there exist minimal difference between the principles of insulin therapy for general diabetic patients and CKD patients. When the glomerular filtration rate (GFR) is between 10-50mL/min/1.73m^2, the total insulin dose administered should be reduced by 25% (Perkovic et al. 2016). However, when the GFR is 10ml/min, the dose should be reduced by 50% that of the general diabetic patients. As renal failure progresses, proximal tubule should be used to increase the insulin uptake to compensate for decrease in insulin clearance by the kidney. Insulin analogues preparation should be adopted over regular and NPH insulin preparation methods as they are less likely to cause hypoglycemia (Betonico et al 2016). In most cases rapid-acting insulin analogues such as the Lispro, Aspart and Glulisine are ideal for quick correction of elevated blood sugars as they are renal impairment does not affect the pharmacokinetics of insulin analogues in a clinically significant manner.

Metformin is one of the pharmacological treatment popularly used in type 2 patients with reduced GFR. The drug is eliminated through kidney and its clearance rate decreases by 75% once the GFR falls below 60. As such, to minimize the risk of lactic acidosis, various guidelines have advised against using this drug in women and men with serum creatinine of more than 1.4mg/dl and 1.5mg/dl respectively. Although metformin is mainly cleared by the kidneys, the compound level generally remains within the beneficial range minimal increase in lactate concentrations in patients with renal insufficiency of 30-60ml/min, thus making the overall incidence of lactic acidosis manageable (Betonico et al 2016). Clinical studies have also suggested other potential benefits of the drug on macrovascular outcome, even in individuals with prevalent renal contraindications for its use. However, studies shows that an abrupt drop in GFR leads to accumulation metformin. As such, individuals should avoid using metformin in conditions with inherent risk of acute kidney injury such as diarrhoea, dehydration, fever and severe bouts.

Additionally, management of diabetic patients with advanced renal failure and the associated complications include date with protein restriction. In individuals suffering from type 1 diabetes, a dietary pattern in these patients should include whole grains, vegetables, legumes, and carbohydrates from fruits. Besides, carbohydrates should be monitored through counting, exchanges, or experienced –based estimation should be carried out to maintain a stable body weight and glycemic control (Sampanis 2008). Type 2 diabetic patients, on the other hand are normally obese with high insulin resistance and impaired insulin secretion. Ass such, these individuals must be encouraged to lose weight with hypocaloric diet and exercise. Protein restriction is replaced by fat or carbohydrates so as to maintain an adequate caloric intake. However, care should be taken not to increase carbohydrates intake beyond 55% since the patient may develop a condition referred to as hypertriglyceridemia (Kovesdy & Kalantar‐Zadeh 2010). It is also good to note that good dietary management for diabetic patients with CKD calls a partnership between the diabetologist, dietician and nephrologist.

Summarily, management of` complications of diabetes in patients with established renal failure involves both pharmacological and nonpharmacological therapies, with the former including dietary modification, exercise and weight reduction. Pharmacological on the other hand involves use of oral agents such as insulin and other drugs. The two highlighted pharmacological treatments are not exhaustive and exist other drugs such as Glipizide, Repaglinide among others. Besides, glycaemic control is one of the various ways of managing diabetic patients with an end state renal disease (ERSD). ERSD significantly alters glycaemic control and excretion of antidiabetic medications, making the levels of blood glucose to fluctuate thus presenting a challenging to the physicians.

References

1. Betonico, C.C., Titan, S.M., Correa-Giannella, M.L.C., Nery, M. and Queiroz, M., 2016. Management of diabetes mellitus in individuals with chronic kidney disease: therapeutic perspectives and glycemic control. Clinics, 71(1), pp.47-53. Berns, J.S., Glickman, J.D., Golper, T.A., Nathan, D.M., Lam, A.Q. and Mulder, J.E., 2015. Management of hyperglycemia in patients with type 2 diabetes and pre-dialysis chronic kidney disease or end-stage renal disease. Golper T, Nathan D (Ed), Uptodate, Waltham, MA, 2018.[Citado el 8 de diciembre de 2018].
2. Chang, Y.T., Wu, J.L., Hsu, C.C., Wang, J.D. and Sung, J.M., 2014. Diabetes and end-stage renal disease synergistically contribute to increased incidence of cardiovascular events: a nationwide follow-up study during 1998–2009. Diabetes care, 37(1), pp.277-285.
3. Hahr, A.J. and Molitch, M.E., 2015. Management of diabetes mellitus in patients with chronic kidney disease. Clinical diabetes and endocrinology, 1(1), p.2.
4. Kovesdy, C.P., Park, J.C. and Kalantar‐Zadeh, K., 2010, March. Glycemic control and burnt‐out diabetes in ESRD. In Seminars in dialysis (Vol. 23, No. 2, pp. 148-156). Oxford, UK: Blackwell Publishing Ltd.
5. Perkovic, V., Agarwal, R., Fioretto, P., Hemmelgarn, B.R., Levin, A., Thomas, M.C., Wanner, C., Kasiske, B.L., Wheeler, D.C., Groop, P.H. and Bakris, G.L., 2016. Management of patients with diabetes and CKD: conclusions from a “Kidney Disease: Improving Global Outcomes”(KDIGO) Controversies Conference. Kidney international, 90(6), pp.1175-1183.
6. Sampanis, C.H., 2008. Management of hyperglycemia in patients with diabetes mellitus and chronic renal failure. Hippokratia, 12(1), p.22.
7. Wang, A.Y.M., 2011. Cardiovascular risk in diabetic end‐stage renal disease patients. Journal of diabetes, 3(2), pp.119-131.

Diabetes is a continual metabolic ailment that renders the physique the lack of ability to method enough amount or cannot advance of insulin. Insulin is naturally made pancreatic hormone that helps meals glucose get into the cells for electricity consumption. So the insulin inside your body is now not being used, ensuing in glucose to be dormant and no longer attaining the cell, stopping blood sugar ranges entering a hypoglycemic/ hyperglycemic state. Hypoglycemia is a nation the place the body’s sugar stages are too low because lack of food energy accomplishing our cells in order to characteristic and hyperglycemia is when the body’s level of sugar too excessive the oversaturation of meals energy. Two kinds of diabetes exist kind one and kind two. Type two Diabetes being the most common. There are extra adults with type one than there are children.

Type two diabetes is the result of your body now not sufficiently use or create insulin. A component that may additionally have an effect on a character is that household history can make bigger the risk of inheriting kind one diabetes. People of sure types of race are in greater hazard for unsure logic. High blood sugar levels, either from a lack of insulin, influences the body’s functionality to get glucose from the blood into cells to fulfil electricity wants of the physique causing fatigue

Excess glucose builds up in the blood, whilst the kidneys cannot preserve up with filtering and absorbing the extra sucrose in a person’s body and therefore excreted urine is regularly and leaves you with polydipsia Over time being hyperglycemic impacts the nerves neuropathy, leading to negative blood circulation making the restoration system for wounds longer and growing the risk of infections.

Long time period uncontrolled High Blood sucrose impacts the capacity to see via adverse the small blood vessels over the retina creating a blurry vision for the person numbness, loss of sensation, ache in feet, legs, arms are due to chronic hyperglycemia, known as Peripheral neuropathy or nerve damage Uncontrolled diabetes being hyperglycemic motives the blood entry denial due to the cell due to lack of insulin and barring insulin the physique cannot convert food fed on to be energy. With strength deficiency causes starvation and therefore leaving the person with Polyphagia. (to have immoderate starvation or increased appetite)

Complications with diabetes is Macrovascular complications. In some cases atherosclerosis starts offevolved to slim arterial partitions in the course of the body, from any damage towards the coronary vascular. Diabetes will increase the threat for cardiovascular disease, and CVD is the best element of health care outlay. Study has shown Microvascular complications has over 10,000 new cases of blindness each and every year in the United states due to diabetic neuropathy.Patients with type two diabetes have been observed with extremity of Hypertension and hyperglycemia. Patients with kind one diabetes structure blindness round 20 years of discovery. Anyone with a body mass index greater than 25 is in risk of diabetes.A Glycated Hemoglobin test, acknowledged as A1C, is a blood test that indicates the average blood sugar degree for the past 2-3 months. Measuring the proportion of blood sugar attached to the oxygen carrying protein in purple blood cells. Healthy consuming and bodily endeavor is the most high-quality approaches to manipulate diabetes and typical health. Medication are prescribed orally or by using injection in order to stimulate the pancreas to release and produce insulin. Insulin injections, therapy , pumps are solutions to dealing with insulin delivery. Insulin injection is a straightforward technique of having a needle inject insulin while insulin therapy is a once a week centred mixture shot and an insulin pump is a cellphone cellphone dimension system worn outdoor of the body with a tube connecting the reservoir of insulin to a catheter inserted under the pores and skin of the abdomen.