Example Of Diabetes Research Articles

Reframing Diabetes Prevention: From Body Shaming to Metabolic Reprogramming

This review integrates new developments in psychology with updated physiological insight on the complex relationships among chronic psychological stress (arising from weight stigmatization and body shaming), food composition, physical activity and metabolic health for the example of diabetes. We address how visual measures of health, such as body mass index (BMI) and waist-to-hip ratio, do not adequately capture metabolic health and can instead contribute to weight stigmatization, chronic stress, and system-wide impairment of metabolic health. We also emphasize the importance of food composition over calorie counting. We summarize how chronic stress interacts with nutritional deficiencies and physical inactivity to disrupt the stress response, immune response, gut microbiome, and function of fat depots. We specifically address how interactions among lifestyle factors and the gut microbiome regulate whether fat stored around the waist has a negative or positive effect on metabolic health. We aim to provide a resource and updated framework for diabetes prevention and health promotion by (i) highlighting metabolic imbalances triggered by lifestyle changes during the transition to industrialized society and (ii) detailing the potential to support metabolic health through access to modest, but comprehensive lifestyle adjustments.

Associating pathways with diseases using single-cell expression profiles and making inferences about potential drugs.

Finding direct dependencies between genetic pathways and diseases has been the target of multiple studies as it has many applications. However, due to cellular heterogeneity and limitations of the number of samples for bulk expression profiles, such studies have faced hurdles in the past. Here, we propose a method to perform single-cell expression-based inference of association between pathway, disease and cell-type (sci-PDC), which can help to understand their cause and effect and guide precision therapy. Our approach highlighted reliable relationships between a few diseases and pathways. Using the example of diabetes, we have demonstrated how sci-PDC helps in tracking variation of association between pathways and diseases with changes in age and species. The variation in pathways-disease associations in mice and humans revealed critical facts about the suitability of the mouse model for a few pathways in the context of diabetes. The coherence between results from our method and previous reports, including information about the drug target pathways, highlights its reliability for multidimensional utility.

Diyabet Hastalığı Örneğinde Kronik Hastalar ve Hasta Yakınlarıyla İletişim

Aim: The presentation of information that is thought to be useful for physicians in communication with chronic patients and their relatives through the example of diabetes. Materials and methods: Prepared by the traditional review method. The importance of communication with chronic patients and their relatives, how to establish appropriate communication and sampling through diabetes is explained and summarized based on the literature. Results: Chronic diseases, defined as prolonged and slowly progressive diseases are the most important health problems of the 21st century. In 2015, non-communicable deaths increased, reaching 70%. Chronic diseases have not only become a problem in developed countries but have become the first health problem in all countries according to world mortality and morbidity data. Self-care of patients is as important as medical treatment in the course of treatment of chronic diseases. When chronic patients are informed and involved in the decision-making process, they can adapt more easily to medical advice, take on more self-care and their health outcomes improve. Since chronic diseases require lifelong care, this process involves difficulties for relatives of the patients, and their relatives may experience physical and psychosocial problems and may need support and care. Diabetes is one of the most complex, most important chronic diseases that require continuous health care, and, like other chronic diseases, patients and their relatives may experience similar problems. The frequency of diabetes increased by 90%, from 7.7% to 13.7% between 1997 to 2010. It ranks 8th among all causes of death in the world and causes premature deaths due to myocardial infarction and stroke. It is known that 42.4% of the population over the age of 20 have diabetes or prediabetes. Conclusions: Correct and adequate communication between physicians and chronic patients and their relatives is among the most important elements in the management of all chronic diseases including diabetes. Giving special attention to this issue in both pre- and post-graduaion medical education will also contribute to raising awareness and sensitivity on the subject and will have positive reflections on the practices.

Biological influences on health-ratings: The relationship of self-rated health, biomarkers, and diabetes and how it differs across groups

Introduction Self-ratings of health (SRH) are the most widely used single-indicator of health in many scientific disciplines as well as in epidemiology. Accordingly, many researchers rely on SRH in describing, examining, and explaining (social) inequalities in health. How these ratings come about, however, is still relatively unexplored. For instance, little is known about the extent to which undiagnosed diseases or the severity of present diseases play a role in rating one's health. Biomarkers, such as HbA1c for diabetes, play an interesting role in this regard since they give objective and highly relevant health information beyond what a respondent is willing - or able - to tell. Thus, they offer the possibility of investigating the relevance of diseases unknown to respondents or the severity of diseases. Methods Through the example of diabetes and the pertinent lab-measured HbA1c-concentration in the respondents’ blood, this paper analyzes the relative roles of diagnoses and biomarkers in the evaluation of general health. To do so, this paper draws on diverse health data from 2890 respondents aged 50–79 collected in the 2007 and 2009 waves of the Canadian Health Measures Survey (CHMS). The paper quantifies and compares the contribution of self-reported diagnoses of diabetes and biomarker-indicated diabetes, undiagnosed diabetes, prediabetes, and diabetes-severity to explaining SRH. Their contributions are compared between genders, age, and education. Additionally, separate analyses of all 359 self-reportedly diagnosed diabetics in the sample were conducted in order to investigate the role diabetes-severity plays within diabetics when rating their health. Results Across all subgroups, the influence of undiagnosed (pre)diabetes as well as HbA1c on SRH appears to be subordinate to a manifest diagnosis of diabetes. With the exception of older men (aged 65–79), all models show a greater influence of diagnoses than lab-indicated diabetes while lab-indicated prediabetes generally does not affect SRH when controlling for other health indicators. General and subgroup analyses of the influence of severity within diabetics reveal that HbA1c indeed influences diabtetics’ SRH, although only for older respondents (65 + ) as well as respondents with at least post secondary education. Conclusions While further research is needed, these results highlight the importance of diagnoses of chronic diseases in rating one's health. This paper also suggests that SRH is primarily based on information known to and relevant for the daily lives of respondents while undiagnosed diseases and disease-severity are - at least in the case of diabetes - less relevant.

Multiple causes of death analysis of chronic diseases: the example of diabetes.

BackgroundIdentifying a single disease as the underlying cause of death (UCOD) is an oversimplification of the clinical-pathological process leading to death. The multiple causes of death (MCOD) approach examines any mention of a disease in death certificates. Taking diabetes as an example, the study investigates: patterns of death certification, differences in mortality figures based on the UCOD and on MCOD, factors associated to the mention of diabetes in death certificates, and potential of MCOD in the analysis of the association between chronic diseases.MethodsThe whole mortality archive of the Veneto Region-Italy was extracted from 2008 to 2010. Mortality rates and proportional mortality were computed for diabetes as the UCOD and as MCOD. The position of the death certificate where diabetes was mentioned was analyzed. Conditional logistic regression was applied with chronic liver diseases (CLD) as the outcome and diabetes as the exposure variable. A subset of 19,605 death certificates of known diabetic patients (identified from the archive of exemptions from medical charges) was analyzed, with mention of diabetes as the outcome and characteristics of subjects as well as other diseases reported in the certificate as predictors.ResultsIn the whole mortality archive, diabetes was mentioned in 12.3 % of death certificates, and selected as the UCOD in 2.9 %. The death rate for diabetes as the UCOD was 26.8 × 105 against 112.6 × 105 for MCOD; the UCOD/MCOD ratio was higher in males. The major inconsistencies of certification were entering multiple diseases per line and reporting diabetes as a consequence of circulatory diseases. At logistic regression the mention of diabetes was associated with the mention of CLD (mainly non-alcohol non-viral CLD). In the subset of known diabetic subjects, diabetes was reported in 52.1 %, and selected as the UCOD in 13.4 %. The probability of reporting diabetes was higher with coexisting circulatory diseases and renal failure and with long duration of diabetes, whereas it was lower in the presence of a neoplasm.ConclusionsThe use of MCOD makes the analysis of mortality data more complex, but conveys more information than usual UCOD analyses.

Knowledge is power if you hone it

Diabetes has become one of the major global public health problems of this new millennium. There is dire need for truthful “Continuing Medical Education” for healthcare professional of all shades and spectrum to be aware of their historical role to provide necessary advices on Diabetes to their stakeholders at every intersection. Let us not place the fate of average Indians at the mercy of health care providers who are too busy to get time to be updated regarding preventive measures to reduce prevalence and downstream complications of this “silent” killer. The unremitting progressions of the concepts of diet and nutrition issues amid lifestyle management need to be internalized and advocated in the light of holistic approaches to the management to the diabetics on one hand and caregivers as well as nondiabetics on the other hand. The authors wish to emphasize on the importance of philosophy of the voluntary and perpetual updating of knowledge, on diet and appropriate lifestyle, of the health care providers of all shades and all levels for our mission and vision of health promotion with the example of diabetes at this juncture. Key words: Diabetes, diet, nutrition

A new measure of multimorbid illness and treatment representations: The example of diabetes and depression

BackgroundDepression is two to three times more common in people with diabetes than in the general population. Although multimorbid diabetes and depression is associated with poor health outcome, existing research has focused on patients׳ understanding and management of each condition in isolation. This study describes the development and validation of the Diabetes and Depression Representation and Management Questionnaire (DDRMQ), a measure of understanding, management and medication beliefs in people with diabetes and depression. MethodsIn Study 1, DDRMQ items were developed through further analysis of an earlier qualitative study and refined through 18 cognitive interviews. In Study 2, 334 adults with diabetes and depression from general practices, diabetes clinics and support groups completed the DDRMQ, demographic questions and validating measures. ResultsFactor analysis of the DDRMQ using principal axis factoring resulted in a 35 item scale organised into ten subscales. The modified measure had adequate internal and test–retest reliability. Initial evidence of construct validity was also demonstrated. LimitationsLow participant response rates and the high percentage of well-educated white participants limit the generalisability of results. As Study 2 was cross-sectional, future research is needed to establish if different ways of thinking about and managing diabetes and depression can predict patient outcome. ConclusionsThe DDRMQ is the first measure of patient understanding, management and medication beliefs in people with established diagnoses of both diabetes and depression. The DDRMQ will facilitate an increased awareness of the patient experience of diabetes and depression and help inform patient centred care and intervention development for people with multiple conditions.

Estimating Population Benefits Using a Risk Tool: An Example of Diabetes in Canada

Estimating Population Benefits Using a Risk Tool: An Example of Diabetes in Canada

Why Patients Should Be More Empowered: A European Perspective on Lessons Learned in the Management of Diabetes

Patient empowerment has emerged as a new paradigm that can help improve medical outcomes while lowering costs of treatment. The concept seems particularly promising in the management of chronic diseases. Diabetes may provide a blueprint for implementing patient empowerment because empowering patients has been instrumental in achieving the successes we have witnessed in the management of diabetes in recent decades. Looking at the example of diabetes, this article investigates the role and contribution of patient empowerment to therapy success and derives actions that need to be taken in order to fully leverage the potential of this concept for patients, health care professionals, and health systems.

Preferences of diabetes patients and physicians: a feasibility study to identify the key indicators for appraisal of health care values.

BackgroundEvidence-based medicine, the Institute of Medicine (IOM) and the German Institute for Quality and Efficiency in Health Care (IQWiG), support the inclusion of patients' preferences in health care decisions. In fact there are not many trials which include an assessment of patient's preferences. The aim of this study is to demonstrate that preferences of physicians and of patients can be assessed and that this information may be helpful for medical decision making.MethodOne of the established methods for assessment of preferences is the conjoint analysis. Conjoint analysis, in combination with a computer assisted telephone interview (CATI), was used to collect data from 827 diabetes patients and 60 physicians, which describe the preferences expressed as levels of four factors in the management and outcome of the disease. The first factor described the main treatment effect (reduction of elevated HbA1c, improved well-being, absence of side effects, and no limitations of daily life). The second factor described the effect on the body weight (gain, no change, reduction). The third factor analyzed the mode of application (linked to meals or flexible application). The fourth factor addressed the type of product (original brand or generic product). Utility values were scaled and normalized in a way that the sum of utility points across all levels is equal to the number of attributes (factors) times 100.ResultsThe preference weights confirm that the reduction of body weight is at least as important for patients - especially obese patients - and physicians as the reduction of an elevated HbA1c. Original products were preferred by patients while general practitioners preferred generic products.ConclusionUsing the example of diabetes, the difference between patients' and physicians' preferences can be assessed. The use of a conjoint analysis in combination with CATI seems to be an effective approach for generation of data which are needed for policy and medical decision making in health care.

Influence of control selection in genome-wide association studies: the example of diabetes in the Framingham Heart Study

Epidemiologic study designs represent a major challenge for genome-wide association studies. Most such studies to date have selected controls from the pool of participants without the disease of interest at the end of the study time. These choices can lead to biased estimates of exposure effects. Using data from the Framingham Heart Study (Genetic Analysis Workshop 16 Problem 2), we evaluate the impact on genetic association estimates for designs with control selection based on status at the end of a study (case exclusion (CE) sampling) to control selection based on incidence density (ID) sampling, when controls are selected from the pool of participants who are disease-free at the time a case is diagnosed. Cases are defined as those diagnosed with type 2 diabetes (T2D). We estimated odds ratios for 18 previously confirmed T2D variants using 189 cases selected by ID sampling and using 231 cases selected by CE sampling. We found none of these single-nucleotide polymorphisms to be significantly associated with T2D using either design. Because these empirical analyses were based on a small number of cases and on single-nucleotide polymorphisms with likely small effect sizes, we supplemented this work with simulated data sets of 500 cases from each strategies across a variety of allele frequencies and effect sizes. In our simulated datasets, we show ID sampling to be less biased than CE, although CE shows apparent increased power due to the upward bias of point estimates. We conclude that ID sampling is an appropriate option for genome-wide association studies.

Guidance on delivering effective group education

Group education is increasingly being advocated in place of the traditional one to one approach in health care. Using the example of diabetes, this article describes why group education is effective, and outlines a process that can help shape a group education programme. Identifying the purpose of a programme, understanding how people learn, and behaviour change techniques, all help the educator identify what are the important elements to include. Planning the process of a programme to enhance its success, and developing an evaluation strategy to measure success, are also included.

Current situation of screening for cancer

The large majority of human cancer diagnosed each year may be avoidable, but avoidable causes of many common cancers have not yet been clearly identified. A prerequisite of cancer prevention lies in identifying the determinants of cancer risk. Cancer control embraces a number of important elements with the aim of reducing the incidence of cancer and, failing primary prevention, reducing mortality either by finding disease at an earlier and more ‘curable’ stage or by improving the survival stage-for-stage through improvements in therapy. There are a number of disciplines involved within this embrace including epidemiology, clinical science, behavioural science and health education. It is a complex, and at times, uncoordinated package. Screening for cancer involves the examination of, but more frequently the performance of a test on, asymptomatic individuals in order to classify them as likely or unlikely to have the disease in question. Those who appear likely to have the disease are investigated further to arrive at a final diagnosis and those who are found to have the disease are treated. The organized application of early diagnosis and treatment activities in large groups is often described as population screening. The goal of screening generally is to reduce mortality from the disease among the people screened by early treatment of the cases discovered. Screening calls attention to the likelihood of disease before symptoms appear. Screening in connection with early diagnosis and treatment should be clearly distinguished from other uses of the term in epidemiology and clinical practice. In particular, ‘screening’ is commonly used to describe a series of tests done on a symptomatic patient for whom a diagnosis is not yet established. This type of screening is part of the practice of clinical medicine rather than public health or preventive medicine. Screening procedures may also be used to estimate the prevalence of various conditions without immediate disease-control objectives. Screening could be used both to refer to the identification of people at high risk of a disease but who do not yet have it and to the application of tests to this group for the early detection of disease. It is also important to distinguish between diagnostic tests and screening tests. Morrison [1] illustrates this using the example of diabetes. The use of a glucose tolerance test is considered to be a diagnostic test while use of the (random) blood sugar method may be considered a screening test. Thus a liver biopsy would be considered a diagnostic test for liver cancer and a biopsy of the prostate a diagnostic test for prostate cancer. It is also essential to distinguish between what is meant by ‘screening’ and ‘case-finding’. Screening is aimed at the general population and not merely those who have sought some medical attention. The criteria which should be fulfilled before screening for a particular form of cancer were outlined by Wilson and Jungner [2] (Table 1). These criteria cover a variety of issues including the utility and acceptability of the screening test, knowledge of the natural history and treatment outcome of cancer and the cost, economical and due to treatment and false positive tests. These criteria have stood the test of time.

Globalized, Focused Healthcare?

SUCCESS CAN BE a slippery thing. Sometimes it comes to organizations that focus on depth of offering (e.g., children's book sales, on a specific comer, on a certain side of town). Other times, it comes to superstores that focus on breadth of offering while providing discounts (high customer satisfaction) possible through economies of scale. Yet other times, success comes through enabling technologies like the Internet, which spawned high-tech, high-touch book sales from the convenience of the home. These technologies offer even deeper discounts and broader depth of product lines. So it seems our predictive models depend on which business sector we choose to analyze. Although Herzlinger's article on Dr. Denton Cooley at Texas Heart Institute, it was silent on the equally successful surgery program of Dr. Michael Debakey's heart team operating in a traditional full-service academic medical center, The Methodist Hospital, across Fannin Street in Houston. Dr. Herzlinger's prescription for the future is tantalizing to consider. No one has written or spoken as extensively on the subject of as she has. In its simplest form, focused healthcare is a system of seriously hospitals and neighborhood clinics for treating most major illnesses. Focus brings efficiency, productivity, and efficacy to the treatment of a single disease category. Nonetheless, chronic diseases often do not exist in isolation from other major diseases in the same individual. Chronic patients often present with complex, multiple diseases, such as the diabetic cancer patient. Our nation's hospitals stand ready to address multidisease states of individuals under a single organizational roof To take Herzlinger's argument to an extreme level, we would need to build ten new neighborhood clinics (one for each major disease) throughout town, plus hundreds of small hospitals to replace our current academic medical centers and community hospitals. Several problem areas are likely to arise if our nation universally goes down this pathway. The debt equity required to finance these new structures would be enormous, right at a time when the health provider sector is experiencing a crisis in lowered bond ratings and diminished ability to raise new capital. The example of diabetes brought forward in Dr. Herzlinger's article is worthy of careful scrutiny. According to her analysis, an average state would require $2 billion for a sufficient number of neighborhood clinics and hospitals just for the treatment of diabetes. One can easily compute the enormity of the task to fund such programs in all 50 states for treatment of a number of diverse diseases. Would the traditional practicing physicians and hospitals have to give up all these new revenues to startup firms? If so, a dislocation for physicians, nurses, and hospital workers would occur to a degree never before seen in history. The problem of getting consistent quality in our country is especially well documented by Herzlinger. Every physician leader, administrator, and board member can recite this litany. We are all aware of the problem, and can transform our current practices into the excellence Dr. Herzlinger calls us to, by building on the best practices already emerging in leading organizations around the United States. Focused may be one of the routes to such success, but it is doubtful that model will ever dominate medicine in the United States. The landscape of the future is likely to include large comprehensive medical centers as well as full-service, but less intensive, community and rural hospitals in cooperation with multispecialty physician practices. For me, the end game is efficient, high-quality care that is appropriate and leads to high customer satisfaction. Health systems like Mayo Clinic, Johns Hopkins, Northwestern Memorial, and Henry Ford do not have to be dismantled to get us there. A major tenet of Wanda Jones' paper is that none of us are operating our organizations the same way we did 35 years ago; thus, she concludes that none of us will be operating in the same way in the year 2025. …

Interpreting Hospital Admissions Data Across the Kørner Divide: the Example of Diabetes in the North Western Region

Hospital admission rates and hospital bed utilization rates are presented for all admissions assigned to diabetes mellitus as principal cause in the North Western Region from 1980/81 to 1990/91. Data are derived from Hospital Activity Analysis (1980/81-1986/87) and from the Regional Information System (1988/89-1990/91). Admission rates for all categories of diabetes combined showed little change until 1986/87 after which they rose progressively each year. Hospital bed utilization rates fell progressively from 1986/87 onwards, the number of bed days attributed to diabetes falling from 1.9% to 0.8% of the total for all causes. Most of the rise in admission rates from 1988/89 onwards was attributable to diabetes with ophthalmic complications (ICD 250.4). This was heavily influenced by the enumeration of day cases in the Regional Information System. When these are discounted, admission rates for the more recent years are stable. Diabetes without mention of complications (ICD 250.0) showed the most dramatic decline in its contribution to hospital bed utilization. This may be the result of increasing outpatient support from diabetes specialist nurses whose numbers increased in inverse proportion to the fall in bed utilization attributed to ICD 250.0.

Diabetes mellitus due to viruses--some recent developments.

Many different viruses belonging to several genera have the potential to damage beta cells. The mechanisms they employ are varied, and infection may result in either a direct destruction of islets and rapid insulin deficiency, or in a more gradual loss of functioning islets with the onset of diabetes many years later. Several case histories involving extensive cytolysis of beta cells can be directly linked to viral infection, whilst an example of diabetes occurring many years after viral infection is found in individuals who had a congenital infection with rubella virus. Here, the virus induces an autoimmune reaction against beta cells. Autoimmune phenomena have also been observed in islets following infections with viruses other than rubella, and thus activation of autoimmune mechanisms leading to beta-cell destruction may be a relatively frequent occurrence. Recent evidence shows that picornaviruses are not exclusively lytic, and can induce more subtle, long-term changes in beta cells, which may be important in the aetiology of diabetes. The exact mechanisms involved are not known, but it is clear that several viruses can directly inhibit insulin synthesis and induce the expression of other proteins such as interferons, and the HLA antigens. Strain differences in viruses are important since not all variants are tropic for the beta cells. Several laboratories are in the process of identifying the genetic determinants of tropism and diabetogenicity, especially amongst the Coxsackie B (CB) virus group. The sequence of one such diabetogenic CB4 strain virus has been determined.(ABSTRACT TRUNCATED AT 250 WORDS)