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Impact of Hypoglycemia on Health-Related Quality of Life among Type 2 Diabetes: A Cross-Sectional Study in Thailand.

ABSTRACT: Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases. Patients are generally advised lifestyle changes with antihyperglycemic agents prescribed. The major drawback of prescribing antihyperglycemic agents is the risk of hypoglycemia which subsequently impacts on health-related quality of life (HRQoL). This study is aimed at examining association between previous history of hypoglycemia and HRQoL. The study was a multicenter cross-sectional study, conducted from February 2013 to March 2015 at 5 tertiary care hospitals in Thailand (Srinagarind, Phramongkutklao, Ramathibodi, King Chulalongkorn Memorial, and Siriraj hospitals). The study population were males or females diagnosed with type 2 DM according to ADA criteria, 30 years of age or older, who had been treated with sulfonylurea (SU) monotherapy or SU and metformin combination for at least 6 months. Prespecified medical factors were extracted from medical records 12 months prior to patients' enrolment. The experience of hypoglycemia questionnaire was used to collect and measure severity of hypoglycemia experienced during the previous 6 months. HRQoL was assessed using the 3-level version of EuroQol-5-dimension (EQ-5D-3L) and visual analogue scale (EQ-VAS) questionnaires. Of 659 eligible patients surveyed, 202 patients (30.65%) had experienced symptoms of hypoglycemia. HRQoL was significantly lower among patients reporting at least one of hypoglycemic symptoms, measured by EQ-VAS scores (mean ± SD; 73.66 ± 13.18, 73.56 ± 15.10, or 68.93 ± 14.76 vs. 77.01 ± 13.02, one-way ANOVA; p = 0.006) and EQ-5D-3L index scores (0.62 ± 0.47, 0.68 ± 0.38, or 0.58 ± 0.51 vs. 0.79 ± 0.31, one-way ANOVA; p < 0.001) for mild, moderate, or severe/very severe hypoglycemic patients compared with patients without hypoglycemic symptoms. After adjusting for confounding factors in a multiple linear regression model, patients with hypoglycemic symptoms either mild, moderate, or severe/very severe demonstrated significantly higher impairment for EQ-VAS and EQ-5D indexes than those who did not experience hypoglycemic symptoms. In conclusion, our study showed decreased HRQoL determined by EQ-5D and EQ-VAS in patients reporting symptoms of hypoglycemia compared with patients not reporting hypoglycemic symptoms, relative to severity of hypoglycemia.

SUBMITTER: Pratipanawatr T

PROVIDER: S-EPMC6854960 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHealth-related quality of life and glycaemic control are some of the central outcomes in clinical diabetes care and research. The purpose of this study was to describe the health-related quality of life and assess its association with glycaemic control in adults with type 1 and type 2 diabetes in a nationwide setting.MethodsIn this cross-sectional survey, people with type 1 (n = 2479) and type 2 diabetes (n = 2469) were selected at random without replacement from the Swedish National Diabetes Register. Eligibility criteria were being aged 18-80 years with at least one registered test of glycated haemoglobin (HbA1c) the last 12 months. The generic 36-item Short Form version 2 (SF-36v2) was answered by 1373 (55.4%) people with type 1 diabetes and 1353 (54.8%) with type 2 diabetes.ResultsCorrelation analyses showed weak correlations between scores on the SF-36v2 and glycaemic control for both diabetes types. After the participants were divided into three groups based on their levels of HbA1c, multivariate regression analyses adjusted for demographics, other risk factors and diabetes complications showed that among participants with type 1 diabetes, the high-risk group (≥70 mmol/mol/8.6%) had statistically significantly lower means in five out of eight domains of the SF-36v2 and the mental component summary measure, as compared with the well-controlled group (< 52 mmol/mol/6.9%). Among the participants with type 2 diabetes, the high-risk group had the lowest statistically significantly means in seven domains and both summary measures.ConclusionsAmong people with type 1 and type 2 diabetes, adults with high-risk HbA1c levels have lower levels of health-related quality of life in most but not all domains of the SF-36v2. This finding was not explained by demographics, other risk factors, or diabetes complications. The weak individual-level correlations between HRQOL scores and levels of glycaemic control argues for the need to not focus exclusively on either HbA1c levels or HRQOL scores but rather on both because both are important parts of a complex, life-long, challenging condition.

Project description:BackgroundDiabetes is accompanied by a marked reduction in patient's quality of life (QOL) and leads to higher disability-adjusted life years than most diseases. Depression further deteriorates QOL and is associated with poor treatment outcomes and lowered glycemic control in diabetes. We analysed the QOL and depression among the people living with diabetes in Nepal.MethodsWe conducted a cross-sectional survey among a random sample of 157 diabetic patients visiting diabetes clinic at a major teaching hospital in Kathmandu, Nepal. We administered the Nepali version of WHO-BREF for face to face interviews to obtain data on QOL scores. The Nepali version of Patient Health Questionnaire-9was also used to record responses on depression items.ResultsMore than half of the respondents (54.1%) experienced depression with mean PHQ-9 score of 6.15 ± 5.01 on a scale of 0-27. On a scale of 0 to 100, highest QOL mean score was reported in social relationship domain (57.32 ± 11.83), followed by environment domain (54.71 ± 7.74), psychological health (53.25 ± 10.32) and physical health (50.74 ± 11.83). After adjusting for other covariates, urban residence decreased the physical health score by 4.74 (? = -4.74, 95% CI: -8.664,-0.821), social relationship domain score by 3.420 (? = -3.420, 95% CI: -6.433,-0.406) and the overall QOL by 2.773 (? = -2.773, 95% CI: -5.295,-0.252). Having diagnosed with diabetes since more than 10 years increased physical health by 5.184 score points (? = 5.184; 95% CI: 0.753, 9.615).Similarly, having severe depression decreased social relation domain score by 6.053 (? = -6.053, 95% CI:-11.169,-.936).ConclusionHaving urban residence significantly decreased the physical health and social relation domain scores as well as the overall QOL scores. Similarly, having diagnosed since more than 10 years increased physical health domain score. Severe depression decreased social relationship domain score. Since depression affects QOL, we suggest early diagnosis and prompt treatment of depression in T2DM people as part of their routine primary care in Nepal.

Project description:BACKGROUND: Despite certain contradictions, an association has been identified between adherence to drug treatment and the quality of life in patients with type 2 diabetes. The contradictions observed emphasize the importance of using different methods to measure treatment adherence, or the association of psychological precursors of adherence with quality of life. For this reason, we have used an indirect method to measure adherence (pill count), as well as two adherence behaviour precursors (attitude and knowledge), to assess the association between adherence and the quality of life in type 2 diabetes patients. METHODS: A cross-sectional comparative study on a random sample of 238 type 2 diabetic patients was carried out over one year in four family medicine units of the Mexican Institute of Social Security (IMSS) in Aguascalientes, Mexico. Treatment adherence was measured using the indirect method of pill count to assess adherence behaviour, obtaining information at two home visits. In the first we recorded the medicine prescribed and in the second, we counted the medicine remaining to determine the proportion of the medicine taken. We also assessed two adherence behaviour precursors: the patients' knowledge regarding their medical prescription measured through a structured questionnaire; and attitudes to treatment adherence using a Likert scale. Quality of life was measured through the WHOQOL-100 (the WHO Quality of Life questionnaire). Information concerning both knowledge and attitude was obtained through interviews with the patients. A multiple linear regression model was constructed to establish the relationship between each quality of life domain and the variables related to adherence, controlling for covariates. RESULTS: There was no association between quality of life and treatment adherence behaviour. However, the combination of strong knowledge and a positive attitude was associated with five of the six quality of life domains. CONCLUSION: The results suggest that it is important to explore psychological precursors of treatment adherence behaviour in type 2 diabetic patients. Indeed, we consider that it will be useful to carry out interventions that change negative attitudes towards treatment adherence and that promote medical prescription knowledge, which may help to improve the quality of life of such patients.

Project description:BACKGROUND:Orthodontic braces have become symbols of wealth and fashion accessories in some parts of the world. However, there is a scarcity of information about the effects of fashion braces on various aspects of quality of life. Therefore, our aim was to investigate the effects of fashion braces on oral health related quality of life (OHRQoL). METHODS:A cross-sectional study was carried out with data collection from a Google form questionnaire distributed in Saudi Arabia via various forms of social media over a period of 4 months. OHRQoL was assessed using the validated Arabic version of the Oral Health Impact Profile-14 (OHIP-14) questionnaire. The fashion braces group included respondents who had braces installed for fashion purposes only. Therapeutic braces group included subjects who were wearing braces to treat any malocclusion problems. Control group included subjects who did not have any kind of braces. People who had previously completed orthodontic treatments were excluded from the study. The negative impacts were divided into seven domains and a total OHIP score was calculated. Statistical analyses and data illustration were performed with SPSS v25 (IBM, NY). RESULTS:A total of 1141 people voluntarily participated in the study. More than 60% of the participants were in the control group while 33.7% had conventional braces for therapeutic reasons and 3.4% had fashion braces. Sociodemographic distributions varied among the groups, with the majority of the fashion braces group having education below the university level and family incomes less than average. There were significant group differences in OHIP domains. Physical pain was the most frequently reported complaint by all subjects and was the highest in the therapeutic braces group. People with therapeutic braces reported significantly higher functional limitation and physical disability than the controls. Fashion braces group reported significantly lower psychological discomfort and disability, social disability and handicap compared to control groups. CONCLUSIONS:The illustrated effects of fashion braces on OHRQoL suggest the need to study the role of social media and educate the public on the use of braces to minimize the negative effects experienced by individuals.

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Impact of Hypoglycemia on Health-Related Quality of Life among Type 2 Diabetes: A Cross-Sectional Study in Thailand.

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