In many African countries, including South Africa, much attention has been centred on the management of HIV/AIDS and tuberculosis epidemics. However, there is growing awareness in South Africa that life-style related non-communicable conditions, such as diabetes and obesity, represent an important health priority (Pirie, 2005:42). The general objective of this study was to evaluate the treatment of diabetic patients in clinics on primary healthcare level and to determine what contributions can be made in the prevention of diabetic complications. The research method consisted out of the selection of the study population, data collection (questionnaire) and the data analysis. There was no structural way of deciding which patients would be selected to be interviewed. As the patients arrived for their appointments the interviewer was informed. No patient was forced to participate in this study and after they agreed to the interview, they signed a consent form that releases the University of any liability that may occur and to give their permission for the interview. The questionnaire was compiled which covered all the aspects of diabetes. This included diagnostic data, life-style, well-being, compliance and monitoring. The researcher completed the questionnaires whilst interviewing the patients. The data obtained from the questionnaires were statistically analysed by using the Statistical Analysis System, SAS 9.1. Effect size, which was given by the Phi coefficient, was used as a descriptive statistic. In this particular study population, the majority of patients were classified as type 2 diabetics. This can be viewed in table 4.8 where 62.14% of the total study population was classified as group B, which means that these patients use oral glucose lowering drugs to control their disease. A further 33.98% of the population was classified as group C diabetics, which means that these patients need oral glucose lowering drugs as well as exogenous insulin to maintain a healthy life. The latter group obviously consists of patients whose diabetic status was not under control in the past, thus the need for the insulin. This clearly shows that these patients have not been informed about how they can manage the disease by dietary modification and lifestyle interventions. Lifestyle, socio-economic and education played a major role in the development of this disease in these patients. The weight status of the study population was determined and can be viewed in table 4.15. Only 20.39% of them were of normal weight with a body mass index (BMI) ranging between 18.5 - 24.9 kg/m2. 39.81% of them were overweight with their BMI ranging between 25 - 29.9 kg/m2 and the remaining 39.81% of the study population were classified as obese with their BMI's above 30 kg/m2. The majority (an estimated 80%) of the study population were above optimal weight. This may cause the development of chronic complications, such as retinopathy, neuropathy and nephropathy. The socio-economic status of the study population was relatively poor because of unemployment. Although 90.07% of them said they had no difficulty to follow their diet (table 4.56) almost half of the patients said they had some difficulty to get the correct food for their specific needs (table 4.53). The first may be because they are still eating they way they used to with no modifications and the latter may be because of their financial status. Not being able to find work has a major effect on their lives. They cannot afford to buy foods suitable for their needs. As previously stated, patient education is fundamental in the managing and controlling diabetes. When these patients were asked whether they know what diabetes is, and what the complications of the disease might hold, most of them answered that it means they have 'sugar', and cannot eat sugary foods any more. This clearly indicates that they did not have a complete knowledge of their disease. After having explained to them in uncomplicated terms what the disease implicates, many of them said it had not been not explained to them previously and that they now understood it better. It was concluded that the majority of the studied population were under a false impression of what diabetes implied. This is partly due to the lack of time the clinic staffs have to spend with each patient, educating them about the disease. One aspect that was most obvious during this study was the fact that an estimated 20% of all patients studied had their own blood glucose monitor (table 4.80). This is somewhat concerning because to have optimal control over one's blood glucose levels, one needs to has a blood glucose monitor for regular monitoring. An estimated 70% of the studied population measures their blood glucose only once a month when they attend the clinic for their monthly visit (table 4.81). This is not nearly enough to ensure optimal control. The average blood glucose levels were calculated and described in section 4.7. Even with the minimal measurement, about 50% of these patients' blood glucose levels were fairly under control with an average of 6-9mmol/L (table 4.88). But the other estimated 50% of the population were not controlled with averages of either below 5mmol/L or above 9mmol/L. This is concerning because the possibility that these uncontrolled cases may develop chronic complications, might be unavoidable unless they start taking control of their lives. And for this to happen, these patients need all the possible education from qualified health care providers and the support of their families. Certain recommendations and restrictions were formulated and discussed. / Thesis (M.Pharm. (Pharmacy Practice))--North-West University, Potchefstroom Campus, 2008.

Aerobic exercise interventions involving individuals with type 1 diabetes have had little positive effect on blood glucose control as reflected by hemoglobin A1c. The few existing interventions involving resistance exercise, either alone or combined with aerobic exercise, while small in sample size, have had better outcomes. The purpose of this research program was to examine the changes in blood glucose levels during activity and for 24 hours post-exercise (as measured by continuous glucose monitoring) when resistance exercise is performed, either on its own or combined with aerobic exercise, as compared to aerobic exercise alone or no exercise. Twelve physically active individuals with type 1 diabetes performed 5 separate exercise sessions in random order separated by at least five days: 1) no exercise/control; 2) aerobic exercise (45 minutes of treadmill running at 60% VO2peak); 3) resistance exercise (45 minutes of weight lifting – 3 sets of 8 repetitions of 7 different exercises); 4) aerobic then resistance exercise (2 and 3 combined with the aerobic exercise first); 5) resistance then aerobic exercise (2 and 3 combined with the resistance exercise first). We found that resistance exercise was associated with a lower risk of hypoglycemia during exercise, less carbohydrate intake during exercise, less post-exercise hyperglycemia and more frequent (but less severe) nocturnal hypoglycemia than aerobic exercise. When aerobic and resistance exercise were combined, performing resistance exercise prior to aerobic exercise (rather than the reverse) resulted in attenuated declines in blood glucose during aerobic exercise, accompanied by a lower need for carbohydrate supplementation during exercise and a trend towards milder post-exercise nocturnal hypoglycemia.

In many African countries, including South Africa, much attention has been centred on the management of HIV/AIDS and tuberculosis epidemics. However, there is growing awareness in South Africa that life-style related non-communicable conditions, such as diabetes and obesity, represent an important health priority (Pirie, 2005:42). The general objective of this study was to evaluate the treatment of diabetic patients in clinics on primary healthcare level and to determine what contributions can be made in the prevention of diabetic complications. The research method consisted out of the selection of the study population, data collection (questionnaire) and the data analysis. There was no structural way of deciding which patients would be selected to be interviewed. As the patients arrived for their appointments the interviewer was informed. No patient was forced to participate in this study and after they agreed to the interview, they signed a consent form that releases the University of any liability that may occur and to give their permission for the interview. The questionnaire was compiled which covered all the aspects of diabetes. This included diagnostic data, life-style, well-being, compliance and monitoring. The researcher completed the questionnaires whilst interviewing the patients. The data obtained from the questionnaires were statistically analysed by using the Statistical Analysis System, SAS 9.1. Effect size, which was given by the Phi coefficient, was used as a descriptive statistic. In this particular study population, the majority of patients were classified as type 2 diabetics. This can be viewed in table 4.8 where 62.14% of the total study population was classified as group B, which means that these patients use oral glucose lowering drugs to control their disease. A further 33.98% of the population was classified as group C diabetics, which means that these patients need oral glucose lowering drugs as well as exogenous insulin to maintain a healthy life. The latter group obviously consists of patients whose diabetic status was not under control in the past, thus the need for the insulin. This clearly shows that these patients have not been informed about how they can manage the disease by dietary modification and lifestyle interventions. Lifestyle, socio-economic and education played a major role in the development of this disease in these patients. The weight status of the study population was determined and can be viewed in table 4.15. Only 20.39% of them were of normal weight with a body mass index (BMI) ranging between 18.5 - 24.9 kg/m2. 39.81% of them were overweight with their BMI ranging between 25 - 29.9 kg/m2 and the remaining 39.81% of the study population were classified as obese with their BMI's above 30 kg/m2. The majority (an estimated 80%) of the study population were above optimal weight. This may cause the development of chronic complications, such as retinopathy, neuropathy and nephropathy. The socio-economic status of the study population was relatively poor because of unemployment. Although 90.07% of them said they had no difficulty to follow their diet (table 4.56) almost half of the patients said they had some difficulty to get the correct food for their specific needs (table 4.53). The first may be because they are still eating they way they used to with no modifications and the latter may be because of their financial status. Not being able to find work has a major effect on their lives. They cannot afford to buy foods suitable for their needs. As previously stated, patient education is fundamental in the managing and controlling diabetes. When these patients were asked whether they know what diabetes is, and what the complications of the disease might hold, most of them answered that it means they have 'sugar', and cannot eat sugary foods any more. This clearly indicates that they did not have a complete knowledge of their disease. After having explained to them in uncomplicated terms what the disease implicates, many of them said it had not been not explained to them previously and that they now understood it better. It was concluded that the majority of the studied population were under a false impression of what diabetes implied. This is partly due to the lack of time the clinic staffs have to spend with each patient, educating them about the disease. One aspect that was most obvious during this study was the fact that an estimated 20% of all patients studied had their own blood glucose monitor (table 4.80). This is somewhat concerning because to have optimal control over one's blood glucose levels, one needs to has a blood glucose monitor for regular monitoring. An estimated 70% of the studied population measures their blood glucose only once a month when they attend the clinic for their monthly visit (table 4.81). This is not nearly enough to ensure optimal control. The average blood glucose levels were calculated and described in section 4.7. Even with the minimal measurement, about 50% of these patients' blood glucose levels were fairly under control with an average of 6-9mmol/L (table 4.88). But the other estimated 50% of the population were not controlled with averages of either below 5mmol/L or above 9mmol/L. This is concerning because the possibility that these uncontrolled cases may develop chronic complications, might be unavoidable unless they start taking control of their lives. And for this to happen, these patients need all the possible education from qualified health care providers and the support of their families. Certain recommendations and restrictions were formulated and discussed. / Thesis (M.Pharm. (Pharmacy Practice))--North-West University, Potchefstroom Campus, 2008.

Thesis (doctoral)--Lund University, 1995. / Added t.p. with thesis statement inserted.

STUDY 1. INTRODUCTION. Insufficient physical activity is a major risk factor for developing type 2 diabetes. Using isotemporal substitution models, the influence of replacing modest durations of sedentary time with physical activity on diabetes risk scores can be studied. The aims of this study were to examine the relationship between diabetes risk scores, sedentary time and physical activity measured using wrist worn accelerometry, and to model the changes in risk scores by reallocating movement behaviours from lower to a higher intensity. METHODS. Data from 251 (93 males; aged 56.7 ± 8.8) participants from a mixed ethnicity cohort from Leicestershire, UK were selected for analysis. The relationship between diabetes risk (using the Leicester Diabetes Risk Assessment Score), physical activity and sedentary time was identified using multiple linear regressions and isotemporal substitution analysis. Models were calculated for main effects and also adjusted for peak oxygen uptake (VO2) and accelerometer wear time. RESULTS. Both unadjusted and adjusted models revealed that diabetes risk was inversely related to sedentary time, and positively related to light and moderate to vigorous physical activity (MVPA) (p < 0.0005). Unadjusted, the replacement of sedentary time with 10 minutes of either light or MVPA resulted in a reduction in diabetes risk score of -0.22 and -0.54, respectively. There was an eight to nine times greater reduction in risk for the same MVPA replacement models when the least active participants were compared to the pooled analysis (3.601 unadjusted). CONCLUSION. Diabetes risk is associated with sedentary time and physical activity estimated from wrist worn accelerometry. The replacement of sedentary time with MVPA is most beneficial for the least active individuals. STUDY 2. INTRODUCTION. Most associations between physical behaviours and health are assessed using intensity and duration based estimations; however, individuals accrue physical activity in differing ways and behavioural profiles have been linked with varying cardiometabolic risk factors. The frequency or regularity of behaviour may hold additional relationships with health, but have not been extensively explored. Accelerometers provide researchers with a large stream of raw data to analyse. The aim of this paper was to calculate a novel method of behavioural regularity called sample entropy from wrist worn accelerometry and to ascertain whether there are associations with cardiometabolic risk factors in adults. METHODS. Data from 290 (107 males; aged 57.0 ± 8.8) participants from a mixed ethnicity cohort from Leicestershire, UK were selected for analysis. Entropy scores were calculated using 60-second count data within MATLAB. The relationship between entropy scores, physical activity, sedentary time and cardiometabolic risk factors was identified using multiple linear regressions. Models were calculated for main effects and also adjusted for age, sex, accelerometer wear time and body mass index (BMI). RESULTS. Sample entropy scores were significantly related to high-density lipoprotein (HDL) cholesterol (b = 0.148, p = 0.042), triglycerides (b = -0.293, p = 0.042) and glycated haemoglobin (HbA1c) (b = -0.225, p = 0.006), even after adjustment for confounding variables. Traditional intensity estimates of physical activity were not associated; however, the frequency of breaks in sedentary time were significantly related to entropy scores (b = 0.004, p = 0.002). CONCLUSION. Using a novel measure of signal complexity, associations have been revealed with cardiometabolic risk factors; however further analysis in a larger, more diverse dataset is required to ascertain the utility of this technique within behavioural research and if so, what constitutes typical/average levels of entropy within a population. STUDY 3. INTRODUCTION. Acute physiological changes such as reductions in postprandial glucose excursions have been demonstrated within experimental studies that have compared being physically active to sedentary conditions. However, for this information to be truly useful, the coupling of behaviour and glucose data in a free-living environment needs to be achieved. The aim of the study was to ascertain if there is a relationship between objectively measured physical activity, sedentary time and glucose variability using glucose monitoring in an adult population. METHODS. Data from 29 participants recruited from a mixed gender sample from Leicestershire, UK were selected for analysis. Physical activity, sedentary time and interstitial glucose was measured continuously over 14 days using an accelerometer and the Freestyle Libre flash glucose monitor. Daily time (minutes) spent sedentary, and in light activity and moderate to vigorous physical activity (MVPA) were regressed against glycaemic variability indices including daily mean (average) glucose, standard deviation and mean amplitude of glycaemic excursions (MAGE). Generalised Estimating Equations were calculated between behaviour and glycaemic variability variables. Models were calculated for main effects and also adjusted for age, gender and accelerometer wear time. RESULTS. Physical activity and sedentary time were associated with measures of glucose variability, however low fitness individuals showed a stronger relationship between MVPA and MAGE (MAGE: whole sample b = -0.002, low fitness b = -0.012. Additionally, after adjustment for covariates, sedentary time was positively associated with a higher daily mean glucose (b = 0.001, p = 0.001) and MAGE (b = 0.002, p < 0.0005) for the low fitness group. MVPA was negatively associated with mean glucose (b = -0.004, p < 0.0005) and MAGE (b = -0.012, p < 0.0005); however, standard deviation of glucose was not associated with behaviour of any intensity. The magnitudes of the relationships were small, although participants were non-diabetics and exhibited relatively good glucose control i.e. minimal fluctuations in daily glucose variability. CONCLUSION. This study shows that sedentary time, physical activity and glucose variability are related. Despite supporting the previous laboratory research, it is uncertain whether any changes in glucose will reliably occur in all individuals. MVPA confers the largest reductions in glucose variability indices, yet as one of the few studies to couple behaviour and glucose data, more research is needed on larger and more diverse samples.

Achieving tight glucose control safely in type 1 diabetes with currently available methods of insulin delivery is challenging. Aggressive regimens carry an increased risk of hypoglycaemia, particularly overnight. Both alcohol consumption and exercise predispose further to low glucose levels. The demands are even greater in pregnancy where, in addition to limiting hypoglycaemia, avoidance of postprandial hyperglycaemia is critical to minimising adverse obstetric outcomes. The aim of my studies was to evaluate feasibility and safety of a closed-loop or ’artificial pancreas’ system linking insulin delivery with continuous glucose monitoring (CGM), in adults with type 1 diabetes in a controlled setting. Three randomised crossover studies compared closed-loop insulin delivery with conventional insulin pump therapy on two separate occasions, matched in meals and activities. During closed-loop visits, CGM values were entered into a computer containing a model predictive control algorithm which advised on basal insulin infusion for subcutaneous delivery, every 15 minutes. During control visits, usual insulin pump regimen was continued. The feasibility study evaluated overnight closed-loop in 12 adults (seven females, mean age 37.7 years, HbA1c 7.8%) following 60g- carbohydrate evening meal. A follow-up study assessed overnight closed-loop in 12 further adults (seven females, mean age 37.2 years, HbA1c 7.8%) following 100g-carbohydrate meal and (mean 564 ml) white wine. The third study evaluated 24 hours of closed-loop in 12 pregnant women (mean age 32.9 years, 19 to 23 weeks gestation, HbA1c 6.4%) during normal daily activities, including low and moderate intensity exercise. Activity and glucose levels were also measured during free-living. CGM performance during exercise was evaluated. Overnight closed-loop insulin delivery in adults, compared with conventional pump therapy, increased time spent with plasma glucose in target range (3.9−8.0 mmol/l) following both standard meal (81% versus 57%; p = 0.012) and large meal accompanied by alcohol (70% versus 46%; p = 0.012). Glycaemic variability, and time spent in hypo- and hyper- glycaemia were lowered. In pregnant women, day and night closed-loop insulin delivery was as effective as usual pump regimen (81% versus 81% time spent with plasma glucose 3.5−7.8 mmol/l; p = 0.754). Hypoglycaemia occurred following exercise, although closed-loop prevented nocturnal episodes. Glycaemic control during free-living was suboptimal, compared with controlled diet and exercise conditions. Accuracy of CGM was lower during exercise. In conclusion, these studies confirm the feasibility and efficacy of overnight closed-loop insulin delivery in adults with type 1 diabetes. Closed-loop is safe during pregnancy and may be beneficial in women with suboptimal glycaemic control. Meals and physical activity currently limit optimal daytime use of closed-loop.

Trata-se de uma pesquisa de avaliação, realizada por análise de resultados antes e após uma intervenção, cujo objetivo principal foi avaliar a contribuição de um programa educativo na monitorização da glicemia capilar, em pessoas com diabetes mellitus tipo 2. A amostra ficou constituída por 82 pessoas, em seguimento ambulatorial em um hospital de atenção terciária do interior paulista. As intervenções educativas foram desenvolvidas em grupo aberto, por meio da ferramenta \"Mapas de Conversação em Diabetes\", fundamentada nos pressupostos da Teoria Social Cognitiva. O programa educativo se desenvolveu em quatro sessões, com duração média de uma hora e quinze minutos para cada tema, respectivamente: fisiopatologia, controle e complicações da doença, alimentação e atividade física, medicamentos e monitorização da glicemia capilar e da insulina. Além destas sessões, ocorreram dois encontros adicionais para a coleta dos dados, o primeiro antes das intervenções e o segundo, após o seu término. No terceiro encontro, enfatizaram-se os cuidados com a monitorização da glicemia capilar, e foram entregues glicosímetros e insumos para a avaliação da glicemia capilar no domicílio. Para a caracterização da amostra, utilizou-se a estatística descritiva, e para as análises dos dados utilizaram-se os testes de McNemar, para as variáveis categóricas, os Testes de Wilcoxon e o de Correlação de Spearman, mediante nível de significância de 5% (alfa = 0,05). Na caracterização da amostra, destacam-se: 48(58,54%) são do sexo feminino, e os respectivos valores médios da idade são 60,4(DP=8,4) anos; dos anos estudados 4,86(DP=3,86) anos e do diagnóstico da doença 15,3 (DP=8,2) anos. Para o valor de p<0,05, houve diferenças entre os momentos para o conhecimento dos cuidados da monitorização (valores da glicemia de jejum e pós-prandial, descarte dos insumos, sinais/sintomas, prevenção e tratamento da hipoglicemia e da hiperglicemia) e da frequência diária da monitorização da glicemia capilar. O programa educativo contribuiu com a melhora do conhecimento e com a frequência da monitorização da glicemia capilar / This was an evaluative study, developed by means of an analysis of results prior to and after an intervention, whose main objective was to evaluate the contribution of an educational program to capillary glucose monitoring in people with type 2 diabetes mellitus. The sample was made of 82 people, in ambulatory follow-up at a hospital that provides tertiary health care in the interior of the state of São Paulo. The educational interventions were developed in an open group, using the tool \"Diabetes Conversation Maps\", grounded on principles of the Cognitive Social Theory. The educational program was developed in four sessions, with an average duration of one hour and fifteen minutes for each subject, namely: physiopathology; disease control and complications; feeding and physical education; medications, capillary glucose monitoring, and insulin. In addition to these sessions, there were also two meetings for data collection; the first was held prior to intervention, and the second after their completion. At the third meeting, the researchers emphasized the care required for monitoring capillary glucose, and handed the participants with glucometers and materials for assessing capillary glucose at home. Descriptive statistics were used for sample characterization. The McNemar test was used for data analysis, and the Wilcoxon test and Spearman\'s correlation for categorical variables, with significance set at 5% (alpha = 0.05). Sample characteristics that stood out include: 48 (58.54%) participants were women, and respective mean values were 60.4 (SD=8.4) years of age; 4.86 (SD=3.86) years of education, and 15.3 (SD=8.2) years since the disease diagnosis. For the value of p<0.05, there were differences among the moments for learning about the monitoring care (interpretation of results, postprandial glucose levels, glucometer calibration, disposal of the materials, cleansing of the puncture site, knowledge of the terms hypoglycemia and hyperglycemia, conducts towards hypoglycemia and prevention of hypoglycemia and hyperglycemia) and the daily frequency of the capillary glucose monitoring. The educational program contributed to improve the knowledge and frequency of capillary glucose monitoring

Four studies investigating the assessment of glycaemic control in cystic fibrosis are presented within this thesis. The first was a validation study of continual glucose monitoring (CGM) in cystic fibrosis (CF). 50 stable adults with CF underwent home CGM for 3 days, during which time they attended the CF centre for OGTT. Gold standard fasting (0 hour) plasma glucose and 2 hour plasma glucose values during OGTT were compared with concurrent CGM sensor glucose values using a 'limits of agreement' analysis. CGM was found to be valid in adults with CF, with its accuracy being consistent with that published in non-CF populations. The next investigation compared OGTT with CGM with several objectives: to determine whether OGTT is a relevant and adequate measure of glycaemia in CF, find out whether CGM could offer a superior alternative to OGTT and explore whether OGTT and CGM results are associated with prior change in lung function and weight in adults with CF. Data from the first study was used to show that the OGTT can only identify abnormal glycaemic control in CF at a late stage, and that CGM is a more relevant reflection of everyday glycaemia in CF. No correlation was found between prior change in lung function and nutritional status in CF and glycaemia measured by OGTT or CGM. The subsequent study investigated whether CGM could identify early abnormal glycaemic control in CF. This involved ten non-CF healthy controls undergoing the same study protocol as the 50 stable adults with CF, to determine 'normal' glycaemic control parameters. Of 25 CF patients with normal glucose tolerance by OGTT, 19 (76%) had significantly higher mean and/or variability of CGM levels than healthy controls. This lead to changes in their management, including 2 subjects being commenced on insulin therapy. The final investigation was a questionnaire study, asking the 50 CF patients to provide information on their experience of undergoing CGM. 58% of patients responded, with replies indicating that they found CGM broadly acceptable, interfering little in their lives and that their experiences were generally positive. This insight into patients' experiences of CGM can be used to guide future clinical and research roles for this tool. These studies have provided novel data regarding the assessment of glycaemic in CF. Information captured by CGM has greater relevance to CF patients' daily lives than OGTT. CGM can identify early problems with glycaemic control leading to changes in management that may not be detected by conventional measures. CGM offers potential in further clinical application and research to improve the lives and outcomes for adults with CF.

Aerobic exercise interventions involving individuals with type 1 diabetes have had little positive effect on blood glucose control as reflected by hemoglobin A1c. The few existing interventions involving resistance exercise, either alone or combined with aerobic exercise, while small in sample size, have had better outcomes. The purpose of this research program was to examine the changes in blood glucose levels during activity and for 24 hours post-exercise (as measured by continuous glucose monitoring) when resistance exercise is performed, either on its own or combined with aerobic exercise, as compared to aerobic exercise alone or no exercise. Twelve physically active individuals with type 1 diabetes performed 5 separate exercise sessions in random order separated by at least five days: 1) no exercise/control; 2) aerobic exercise (45 minutes of treadmill running at 60% VO2peak); 3) resistance exercise (45 minutes of weight lifting – 3 sets of 8 repetitions of 7 different exercises); 4) aerobic then resistance exercise (2 and 3 combined with the aerobic exercise first); 5) resistance then aerobic exercise (2 and 3 combined with the resistance exercise first). We found that resistance exercise was associated with a lower risk of hypoglycemia during exercise, less carbohydrate intake during exercise, less post-exercise hyperglycemia and more frequent (but less severe) nocturnal hypoglycemia than aerobic exercise. When aerobic and resistance exercise were combined, performing resistance exercise prior to aerobic exercise (rather than the reverse) resulted in attenuated declines in blood glucose during aerobic exercise, accompanied by a lower need for carbohydrate supplementation during exercise and a trend towards milder post-exercise nocturnal hypoglycemia.

ABSTRACT Diabetes Mellitus (DM) embraces a group of metabolic diseases which main characteristic is the presence of high glucose levels in blood. It is one of the diseases with major social and health impact, both for its prevalence and also the consequences of the chronic complications that it implies. One of the research lines to improve the quality of life of people with diabetes is of technical focus. It involves several lines of research, including the development and improvement of devices to estimate "online" plasma glucose: continuous glucose monitoring systems (CGMS), both invasive and non-invasive. These devices estimate plasma glucose from sensor measurements from compartments alternative to blood. Current commercially available CGMS are minimally invasive and offer an estimation of plasma glucose from measurements in the interstitial fluid CGMS is a key component of the technical approach to build the artificial pancreas, aiming at closing the loop in combination with an insulin pump. Yet, the accuracy of current CGMS is still poor and it may partly depend on low performance of the implemented Calibration Algorithm (CA). In addition, the sensor-to-patient sensitivity is different between patients and also for the same patient in time. It is clear, then, that the development of new efficient calibration algorithms for CGMS is an interesting and challenging problem. The indirect measurement of plasma glucose through interstitial glucose is a main confounder of CGMS accuracy. Many components take part in the glucose transport dynamics. Indeed, physiology might suggest the existence of different local behaviors in the glucose transport process. For this reason, local modeling techniques may be the best option for the structure of the desired CA. Thus, similar input samples are represented by the same local model. The integration of all of them considering the input regions where they are valid is the final model of the whole data set. Clustering is t / Barceló Rico, F. (2012). Multimodel Approaches for Plasma Glucose Estimation in Continuous Glucose Monitoring. Development of New Calibration Algorithms [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17173 / Palancia