Diabetes-Dependent Quality Of Life Research Articles

Does multifactorial inspiratory muscle training improve postural stability and quality of life of patients with diabetes in Pakistan? A randomised controlled trial

ObjectiveTo determine the effects of multifactorial inspiratory muscle training (IMT) combined with Otago Exercise Programme (OEP) on balance and quality of life (QoL) in patients with diabetes.MethodsPretest–post-test randomised controlled trial.SettingRehabilitation...

Health-Related Quality of Life in Type 2 Diabetes Mellitus Patients at Moi County Referral Hospital in Taita-Taveta County, Kenya

Non-transmittable diseases are becoming a burden in Sub-Saharan Africa due to changing lifestyle habits like smoking, inactivity, and poor diet. Although diabetes was once thought to the affluents-only disease, it is now more commonly seen in low- and middle-income nations like Kenya. The cross-sectional study's goal was to determine socio-demographic and health-related characteristics affiliated to QOL (quality of life) as well as how this condition affected patients with T2DM (type 2 diabetes mellitus) at Moi County Referral Hospital (MCRH) in Taita-Taveta County. were. The study adopted ADDQOL (audit of diabetes dependent quality of life) tool with 19 items version 2006, no alterations were done, and license number HPR4458 was issued to utilize the tool in this study. The 165 patients were picked using a systematic random sampling method. 127(77percent) of the study's participants had a mean quality of life score concerning diabetes of -1.88, roughly corresponding to "quality of life would be much better in the absence of diabetes" at a score of –2. An average weighted impact score of -4.48, indicated an unfavourable impact on the patients' QOL by diabetes mellitus. Foot ulcers/sores (p=0.005; a OR=7.348) and numbness/pain in hands, legs, or feet (p=0.001; a OR=0.155) were associated to low quality of life. The socio-demographic characteristics were not related to the quality of life. The domain-specific element of "sex life" was considered the most essential and negatively impacted at a weighted impact score of -5.14. Overall, quality of life of T2DM patients in MCRH was low. It is important to focus on the often-overlooked health-related characteristics coupled with the disability adjusted life years of diabetic patients and how they both influence their quality of life

Association between glycemic control and patient-reported outcomes in adults with type 1 diabetes in Japan: the SAGE study subanalysis.

Psychosocial aspects and the quality of life (QOL) of individuals with diabetes are important for achieving glycemic control and treatment goals. Here, we describe patient-reported outcomes (PROs) of Japanese adults with type 1 diabetes (T1D) and evaluate the association thereof with glycemic control. This subanalysis of a subgroup of 528 Japanese participants in the SAGE study of adults with T1D used data on glycosylated hemoglobin (HbA1c) and PRO scores [Hypoglycemia Fear Survey-II (HFS-II), Problem Areas In Diabetes (PAID), Insulin Treatment Satisfaction Questionnaire (ITSQ), and Audit of Diabetes-Dependent QOL (ADDQoL)] and summarized the score by the predefined age groups (26-44-years: n = 208, 45-64-years: n = 217, and ≥ 65-years: n = 103). The association between PROs, achieving HbA1c < 7.0%, and individualized targets was explored using multivariate logistic regression analysis. The HFS-II and PAID scores were lower, and the ITSQ score was higher in the ≥ 65-years group than in the younger groups with a linear trend of better scores with increasing age (P for trend < 0.05). ADDQoL scores were similar across the age groups, and present QOL (ADDQoL subscale) tended to improve with age (P for trend < 0.05). Achieving HbA1c < 7.0% and individualized targets were associated with satisfaction with insulin treatment regarding glycemic control. In Japanese adults with T1D, the impact on psychosocial aspects and QOL varied across age groups, with a trend of improving scores with age, potentially in relation to the less stringent glycemic control targets adopted in older individuals. Glycemic control was significantly associated with treatment satisfaction. The online version contains supplementary material available at 10.1007/s13340-023-00668-4.

Assessing the relationship between low-calorie sweetener use and quality of life measures in adults with type 1 diabetes

BackgroundTo evaluate use of low-calorie sweeteners (LCS) among adults with type 1 diabetes (T1D) and its impact on quality of life (QOL).MethodsIn this single center, cross-sectional survey study with 532 adults with T1D, Food related QOL (FRQOL), LCS specific questionnaire (LCSSQ), Diabetes Self-Management Questionnaire (DSMQ), Food Frequency Questionnaire (FFQ), Audit of Diabetes-Dependent QOL (AddQOL), Type 1 Diabetes and Life (T1DAL) questionnaires were administered through RedCAP, a secure, HIPAA-compliant web-based application. Demographics and scores of adults who used LCS in last month (recent users) and others (non-users) were compared. Results were adjusted for age, sex, diabetes duration and other parameters.ResultsOf 532 participants (mean age 36 ± 13, 69% female), 99% heard LCS before, 68% used them in the last month, 73% reported better glucose control with LCS use and 63% reported no health concerns about LCS use. Recent LCS users were older and had a longer diabetes duration and more complications (hypertension, or any complication) than non-users. However, A1c, AddQOL, T1DAL, FRQOL scores did not differ significantly between recent LCS users and non-users. DSMQ scores, DSMQ management, diet, health care scores did not differ between two groups; however, recent LCS users had lower physical activity score than non-users (p = 0.001).ConclusionsMost of the adults with T1D have used LCS and perceived that LCS use improved their QOL and glycemic control; however, these were not verified with questionnaires. There was no difference in QOL questionnaires except DSMQ physical activity between recent LCS users and not users with T1D. However, more patients in need to increase their QOL may be using LCS; therefore, associations between the exposure and outcome can be bi-directional.

122-LB: Impact of Flash Glucose Monitoring on Behavior Modification, Quality of Life, and Treatment Satisfaction in Noninsulin Treated Patients with Type 2 Diabetes

Introduction: CGM's have shown efficacy in the management of patients with T1D and T2D on multiple daily injections (MDI) and insulin pumps as a way to adjust insulin dosing. However, the benefit of CGM could extend beyond the dosing of insulin and has the potential to encourage lifestyle modification in non-insulin treated patients with type 2 diabetes. Methods: This prospective study included flash glucose monitoring-naive adult patients with T2D with and A1c &amp;gt;7% and &amp;lt;9%. Participants were allowed any combination of oral antidiabetic medications and glucagon-like peptide 1 (GLP-1) injections. Participants received study provided Abbott Freestyle Libre for 12 weeks. HbA1c and weight were measured, and the Diabetes Treatment Satisfaction Questionnaire (DTSQ), Audit of Diabetes Dependent Quality of Life (ADDQoL), and Food Frequency Questionnaire were all completed at baseline and 12 weeks. The Experience with Continuous Glucose Monitoring questionnaire was completed at the end of 12 weeks. Results: For participants (n=43) from one single diabetes center, HbA1c improved by 0.37% from 7.70%±0.56 (mean±SD) at baseline to 7.34%±0.57 at 12 weeks (paired t-test=3.65, p=0.0007). Glucose monitoring frequency improved, from 7.4 average number of fingersticks per week (SD: 7.74) to 4.7 flash glucose scans per day (SD: 3.09). Participants also demonstrated some glucose control with their blood sugar reading being within target range 79.44% of the time. Conclusion: The study suggests that FreeStyle Libre in insulin naïve patients with T2D can influence a decrease in A1c. Participants were more aware of their blood sugar levels while using the FreeStyle Libre and were able to achieve greater glycemic control as evidenced by their percent of time in target range. Findings from this study can be used to advocate to insurance companies to cover the Freestyle Libre in T2D patients who do not use insulin. Disclosure M. D. Simmons: None. E. J. Shiffrin: None. Funding Abbott (TJU20-27)

PRODIAB: Perspectives on the use of patient-reported outcome measures among diabetic patients

Patient Reported Outcome Measures (PROMs) are recognized by health authorities as fundamental and can be evaluated by several questionnaires. The main complexity of evaluating PROMs in People with Diabetes (PwD), be it type 1 (PwT1D) or type 2 (PwT2D), is choosing the right tool (generic or specific) with the right constructs. This study explores the use of PROMs in PwD. The main objective was to compare generic and specific QoL PROMs in a diabetic population. The secondary objective was to assess potential overlaps of assessed constructs in the different PROMs frequently used in diabetes.PRODIAB was an online quantitative survey conducted between January and February 2022. The scientific committee selected the following oft-used questionnaires: EuroQol 5-Dimensions 5-Level (EQ-5D-5L), Audit of Diabetes Dependent Quality of Life (ADDQOL), Treatment Burden Questionnaire (TBQ), Hospital Anxiety and-Depression Scale (HADS-A; HADS-D) and Patient-Health-Questionnaire-9 (PHQ-9). All PROMs used were validated in French.Responses from 2,796 French PwD were analyzed. Compared to PwT2D, PwT1D reported a better general Quality of Life (QoL) on the EQ-5D-5L index (0.75 vs 0.66; p < 0.001) and a lower specific QoL on the ADDQOL (-2.8 vs -2.5; p < 0.001). Adjusted analysis showed that age was inversely associated with EQ-5D-5L index score (-0.11; p < 0.001) and a positively associated with ADDQOL score (0.14; p < 0.001). All PROMs were significantly correlated with each other and the HADS-A, HADS-D and PHQ9 (r 0.60 to 0.72) even more so. While principal component analyses suggested that all PROMs measured only one dimension (mental health) (eigenvalue=3.39; first dimension percentage of variance 56.5), adjusted analyses suggested that the EQ-5D-5L is not adequate for assessing the specific impact of diabetes on QoL.Our study emphasizes the importance of identifying the constructs assessed by each PROM as well as the target population in order to choose the best-suited questionnaire type with the most appropriate constructs.

Translation and psychometric properties of the Persian version of the Audit of Diabetes Dependent Quality of Life (IR-ADDQoL)

BackgroundThis study aimed to undertake linguistic validation and assess the psychometric properties of the Persian version of the Audit of Diabetes-Dependent Quality of Life (IR-ADDQoL) questionnaire in Iranian patients with type 1 and type 2 diabetes.MethodsThe gold-standard linguistic-validation procedure required by the developer of the ADDQoL (see https://www.healthpsychologyresearch.com) including cross-cultural adaptation was followed. Validity and reliability of the Persian ADDQoL were then evaluated in a cross-sectional study of a sample of 153 patients with diabetes. Exploratory and confirmatory factor analyses were applied to assess structural validity. Internal consistency reliability was assessed.ResultsBoth forced one-factor and unforced four-factor solutions were extracted from the exploratory factor analysis that jointly accounted for 48% and 66.53% of the variance observed, respectively. Confirmatory factor analysis indicated an acceptable model fit for the Persian ADDQoL. Cronbach’s alpha showed excellent internal consistency for the questionnaire (alpha = 0.931 for the single scale).ConclusionThe Persian ADDQoL (IR-ADDQoL) showed adequate structural validity and excellent internal consistency. Therefore, it could be efficiently used to evaluate the impact of diabetes on quality of life in outcome studies and research settings in Iran.

ODP608 Quality of Life and Treatment Satisfaction in Patients with Type 1 Diabetes Experiencing Different Models of Care in Saudi Arabia

Abstract Background Little is known about the model of care affecting quality of life(QoL)and treatment satisfaction among people with type 1 diabetes(PWT1D). Objectives To compare QoL, treatment satisfaction and cardiometabolic indices among PWT1D receiving different care models in Saudi Arabia. Methods QoL was measure using Audit of Diabetes Dependent Quality of Life(ADDQoL) and treatment satisfaction was measure using Diabetes Treatment Satisfaction Questionnaire status version(DTSQs). Out of 177 respondents to internet validated Arabic versions of ADDQoL and DTSQs,105 are receiving care at specialized diabetes clinics(SDC), whereas 72 are receiving traditional care at general endocrine clinics(GEC). In SDC,where care is delivered jointly by an interdisciplinary team,PWT1D are evaluated from their first visit simultaneously and thereafter as recommended by 6 care providers: diabetes specialist,educator,podiatrist,nutritionist,optometrist, and mental health specialist, while in GEC, PWT1D will be followed every 6-12months and referred to other services as needed where referrals require a long waiting period. ADDQoL and DTSQs scores,sociodemographic characteristics, and cardiometabolic indices were compared between the two groups. The association between patients’ characteristics and their ADDQoL and DTSQs scores were examined. Results Among the respondents,109(61.6%)females,132(74.6%)never married,136(76.8%) belongs to age group(18-30)years old, with a mean duration of diabetes(11.4±7.5years). Both groups are comparable across nearly all sociodemographic characteristics except for half of the SDC attendees reported higher income categories(≥10000 Saudi Riyals)(51.4%vs. 23.6%,p&amp;lt;0. 001). Compared to participants in GEC, larger proportion of participants in SDC use insulin pump(29% vs. 0%, p&amp;lt;0. 0001),continuous glucose monitoring(CGM)(73.3%vs. 13.9%, p&amp;lt;0. 0001),have higher body mass index(26.3±6.4 kg/m2vs. 24.1±5.1 kg/m2,p=0. 016),and lower HbA1c(8.3±1.6%vs. 9.3±2.4%, p=0. 004). Receiving care in SDC is associated with higher DTSQs score(30.5±5.1vs. 26.2±7.9, p&amp;lt;0. 0001),lower level of negative impact of diabetes on ADDQoL score(-2.2±1.9vs. -3.5±2.4, p&amp;lt;0. 0001). Irrespective of clinic type, using insulin pump and CGM is associated with both higher DTSQs score(insulin pump(32±3.9)vs. MDI(28.5±7), p=0. 029), CGM(30.5±5.5)vs. glucometer(27.9±7.1), or not monitoring (22. 0±9.2), p&amp;lt;0. 0001), and lower negative impact of diabetes on ADDQoL score(insulin pump(-1.3±1.1)vs. MDI(-2.9±2.3), p=0. 002),(CGM (-2.3±2.1)vs. glucometer(-3.1±2.4),or not monitoring(-3.5±2.2), p=0. 036). Another factor associated with a higher DTSQs score is: (being never married (29.3±6.5), or married(28.7±7)vs. divorced/widow(20.6±4.7), p=0. 018), whereas other factors associated with lower level of negative impact of diabetes on ADDQoL score are: (younger age(18-30years(-2.5±2.2),or 31-40years(-3.1±2. 0)vs. &amp;gt;40years(-4.4±2.8), p=0. 013)),(being never married(-2.5±2.1)vs. married(-3.4±2.3),or divorced/window(-4.7±3.3), p=0. 010),(having bachelor degree or more (-2.4±1.9) vs. less than bachelor degrees (secondary school(-3.2±2.7),primary school(-3.9± 4.8),intermediate school(-5. 0±2.4), p=0. 005),and(being student(-2.2±1.9)vs. employed(-3.2±2.4), or unemployed(-3.2±2.5), p=0. 010). Conclusion QoL, treatment satisfaction and glycemic control among PWT1D can be enhanced by providing structured care and using devices(insulin pump and CGM). This necessitates a call for healthcare policymakers to utilize the existing health resources to optimize care for PWT1D. Presentation: No date and time listed

Quality of Life for Patients with Type 1 Diabetes Mellitus

Glycemic control is necessary to reduce morbidity and mortality and improving QoL of T1DMM through the prevention and/or delay of these complications. Despite the high susceptibility of Jordanian patients to diabetes and its complications there is scarcity of data in Jordan on the impact of T1DMM on QoL. There is a particular need for research on patients’ perception about QoL and self-care management for T1DMM. Objectives: The aim for this study is to assess QoL in patients' with TIDM and to find out the associations between demographical and QoL among the patients with TIDM. Methods: The study was conducted using a descriptive cross-sectional design, correlation cross-section. The target population for this study was all Jordanian patients who are suffering from T1DMM, while the accessible population will be all adult Jordanian patients who are suffering from T1DMM attending Queen Alia Military Hospital (QAMH). The study instrument included two parts first one the demographical data section. "Audit of Diabetes Dependent Quality of Life (ADDQoL)" was the second element of the instrument used to assess QoL. The SPSS statistics package's programs were used to conduct the statistical analysis (SPSS 24). Results: About 37.3% of survey participants reported that having type 1 diabetes had a negative influence on their quality of life, while 32.9 percent said that their lives would have been better off without the disease. Patients with T1DM showed that the disease had a poor impact on all ADDQoL dimensions. Important associations were perceived between the average weighted impact of ADDQoL values and diabetes complications in T1DM. Diabetes has a noteworthy influence on the quality of life (QoL) of diabetes patients in Jordan, particularly with relation to the liberty to eat and drink. Conclusion: According to the findings of the current study, T1DMM itself has a detrimental impact on patients' quality of life, particularly on their working lives, health status, .......

Effectiveness of the Shenzhuo formula in the treatment of patients with macroalbuminuria secondary to diabetic kidney disease: protocol update and statistical analysis plan

BackgroundDiabetic kidney disease (DKD) is a significant complication of diabetes and has garnered considerable attention. Our previous retrospective study indicated that Shenzhuo formula (SZF) potentially reduces macroalbuminuria secondary to DKD.MethodsThis trial is a 24-week, randomized, multicentric, double-blinded, double-dummy clinical trial. A total of 120 patients with DKD will be equally and randomly divided into two groups: SZF+ irbesartan simulator or irbesartan + SZF simulator. The 24-h urinary protein change from baseline to week 24 is the primary outcome measure. The secondary outcome measures include serum creatinine, estimated glomerular filtration rate, urinary albumin excretion rate, improvement in traditional Chinese medicine symptoms, fasting blood glucose, 2-h postprandial plasma glucose, hemoglobin A1c, cholesterol, triglycerides, high density lipoprotein, low density lipoprotein, blood pressure, albumin to creatinine ratio, and the Audit of Diabetes-Dependent Quality of Life 19. Our recruitment began in May 2015; currently, we have recruited 100 participants, with a designed maximum sample size of 120. The interim results were reviewed at N = 60, and continuing recruitment was recommended. This statistical analysis plan includes our approach to missing data imputation, primary and secondary outcomes analyses, and safety endpoints.DiscussionThis statistical analysis plan will standardize the clinical trial’s statistical analysis and avoid outcome selective reporting bias and data-driven analysis. This trial will provide further clinical evidence regarding the effectiveness of SZF in managing macroalbuminuria secondary to DKD.Trial registrationChinese Clinical Trial Registry ChiCTR-ICR-15006311. Registered on 26 May 2013. http://www.chictr.org.cn/showproj.aspx?proj=10862

Health Related Quality of Life Measurements for Diabetes: A Systematic Review.

Health-related quality of life (HRQOL) is an essential measure that is used to assess the effect of chronic disease management on the health status of an individual. Previous studies have identified various instruments used in the measuring of diabetes-specific health-related quality of life (HRQOL). The aim of this paper is to provide a systematic review of the various instruments used for the diabetes-specific measure of HRQOL, and place emphasis on its content and measurement properties. Methods Preferred Reporting Items for Systematic Reviews and Meta analyses (PRISMA) guidelines was used. A systematic search strategy was used to identify publications reporting diabetes HRQOL measures. The search terms used were: “diabetes quality of life”, “measurements”, and “instruments”. The database that was searched includes PubMed, Science Direct, CINAHL, and Medline. Articles written in the English language and published from January 1990 to December 2020 were included. Those articles that did not measure HRQOL for diabetic patients were excluded. Results: A total of seventeen instruments met the inclusion criteria and included in the review. The appraisal of diabetes scale (ADS), Audit of Diabetes-Dependent QOL measure (ADDQOL), Diabetes Health Profile (DHP), and Problem Areas in Diabetes (PAID) are more suitable for single-scale questionnaires when investigating one or more specific aspects of diabetes-specific quality of life (QOL). The ADDQOL, ADS, Diabetes Impact Measurement Scales (DIMS), Diabetes Quality of Life Clinical Trial Questionnaire (DQLCTQ-R), Malay Version of Diabetes Quality of Life (DQOL), Iranian Diabetes Quality of Life (IRDQOL), Brief Clinical Inventory, and PAID are relevant measures of HRQOL for insulin dependent diabetes mellitus (IDDM) and non-insulin dependent diabetes mellitus (NIDDM) patients. The Asian Diabetes Quality of Life AsianDQOL, The Chinese Short Version of DQOL, Elderly Diabetes Burden Scale (EDBS), Malay Version of Diabetes Quality of Life (DQOL), are relevant measures of HRQOL for NIDDM patients. Only two instruments assess for responsiveness, namely PAID and DQLCTQ-R. In PAID, the effect sizes ranged from 0.32 to 0.65 for interventions. The DQLCTQ-R four domains were responsive to clinical change in metabolic control. Based on this review ADDQOL, DSQOLS, and EDBS psychometric properties are sufficient. Conclusion: Most studies did not check for responsiveness, and future studies should prioritize responsiveness to change, which was not included in the psychometric finding of the reviewed instruments.

Design of an individualised questionnaire to measure the impact of cancer on quality of life: The cancer dependent quality of life (CancerDQoL) questionnaire.

To design an individualised questionnaire to measure the impact of cancer and its treatments on quality of life (QoL). MATERIALS& METHODS: Design of the Cancer-Dependent Quality of Life (CancerDQoL) questionnaire was based on the Audit of Diabetes Dependent QoL (ADDQoL) questionnaire and related -DQoLs for other conditions. Item selection, face validity and content validity were established through clinician and patient ratings of the importance and relevance of 60 domains from the -DQoL Item Library, and semi-structured interviews with 25 English-speaking participants with a range of cancers attending a cancer centre in Zimbabwe (age range: 25-78 years; 16 women, 9 men). Ten interviews were subsequently conducted with UK English-speaking participants with a range of cancers attending Maggie's Centres in London and Dundee (age range: 40-76; 5 women, 5 men) to adapt the CancerDQoL for UK use. The first draft of the CancerDQoL contained 25 domain-specific items from the -DQoL Item Library plus four overview items. Zimbabwean participants indicated that cancer negatively impacted on all life domains included, except 'having children'. Weighted impact (impact ratings multiplied by importance) was most negative for 'sex life', 'depend on others' and 'physical capability'. The least negative weighted impact was found for 'having children', 'spiritual/religious life' and 'past medical/self-care'. UK interviews confirmed no new items were required. Face and content validity of the CancerDQoL is established for an adult sample of English-speaking cancer patients in Zimbabwe and confirmed in an adaptation following UK interviews.

Patient-reported outcomes in adults with type 1 diabetes in global real-world clinical practice: The SAGE study.

To conduct a secondary analysis of the SAGE study to evaluate the association between glycaemic control and patient-reported outcomes (PROs), in adults with type 1 diabetes (T1DM) across different age groups and regions. SAGE was a multinational, cross-sectional, observational study in adults with T1DM. Data were collected at a single visit, analysed according to predefined age groups (26-44, 45-64, and ≥65 years), and reported across different regions. PRO questionnaires were applied to assess hypoglycaemia fear (Hypoglycemia Fear Survey-II), diabetes-related distress (Problem Areas In Diabetes questionnaire), insulin treatment satisfaction (Insulin Treatment Satisfaction Questionnaire), and diabetes-specific quality of life (QoL; Audit of Diabetes-Dependent Quality of Life). Multivariable analysis was performed to evaluate the relationship between glycated haemoglobin (HbA1c) target achievement (<7% and individualised targets) with PRO scores. The PRO scores showed relatively low levels of diabetes-related emotional distress and fear of hypoglycaemia, moderate to high treatment satisfaction, and low diabetes-related impact on QoL. Results were generally comparable across age groups with some regional variability. Achievement of the HbA1c <7% target was associated with less worry about hypoglycaemia, lower diabetes-related emotional distress, higher insulin treatment satisfaction, and higher QoL. Achievement of individualised HbA1c targets was associated with lower diabetes-related emotional distress and higher insulin treatment satisfaction. Better glycaemic control was most closely associated with low emotional distress due to diabetes and high patient-reported insulin treatment satisfaction.

Self-Reported Satisfaction to Treatment, Quality of Life and General Health of Type 2 Diabetes Patients with Inadequate Glycemic Control from North-Eastern Romania.

Type 2 diabetes mellitus (T2DM) undermines health and quality of life (QoL). This cross-sectional study surveyed 138 consenting T2DM patients from North-Eastern Romania with regard to their satisfaction with treatment, diabetes-related impact on QoL, and general health. The Romanian versions of Diabetes Treatment Satisfaction Questionnaire (DTSQ), Audit of Diabetes Dependent Quality of Life (ADDQoL-19), and 36-Item Short Form Health Survey (SF-36) questionnaires were used. Self-reports were analyzed in conjunction with clinical and metabolic profiling. The patients were 57.86 ± 8.82 years old, 49.3% men, treated with oral glucose-lowering drugs, presenting with inadequate glycemic control but without cardiovascular manifestations. The mean DTSQ and ADDQoL scores were 25.46 ± 0.61 and −2.22 ± 1.2, respectively. Freedom to eat, holidays, journeys, leisure, physical health, sex life, freedom to drink, and feelings about the future scored below average. The mean SF-36 physical and mental health scores were 47.78 ± 1.03 and 50.44 ± 1.38, respectively. The mean SF-6D score was 0.59 ± 0.04 (generated retrospectively using SF-36 data). Negative associations were significant between ADDQoL, age (r = −0.16), and body mass index (r = −0.23), p < 0.01. Overall scores did not correlate with diabetes duration (except DTSQ, r = −1.18, p = 0.02) or HbA1c. The results confirm other researchers’ findings in Europe and nearby countries. Our patients seemed satisfied with treatment despite glycemic imbalance and viewed diabetes as a burden on QoL and especially freedom to eat.

Quality of life of type 2 diabetes mellitus patients in Ramallah and al-Bireh Governorate\u2013Palestine: a part of the Palestinian diabetes complications and control study (PDCCS)

PurposeType 2 diabetes mellitus (T2DM) is a considerable impact on physical health as well as on emotional and social wellbeing. This study aimed to investigate the quality of life and its associated factors among Palestinians with T2DM.MethodsA cross-sectional study including 517 patients (68% female) was conducted in eleven primary health care clinics located in Ramallah and al-Bireh governorate of the West Bank. To assess socio-demographic data, risk factors and diabetes control, interviews, physical examinations, anthropometric measurements, and blood and urine tests were performed. The validated Arabic version of the Audit of Diabetes-Dependent Quality of Life (ADDQoL) questionnaire was carried out on all patients to measure Quality of Life (QoL). A multivariable regression analysis was performed.ResultsThe average weighted impact (AWI) score was −3.38 (95% CI: −3.55 to −3.21, range: −9.00 to 0.12). This indicates that diabetes was perceived as having a considerable negative impact on the quality of life. The life domains ‘freedom to eat’, ‘physical activities’, and ‘work-life’ were the most negatively impacted. Males and individuals living with diabetes for a prolonged time were associated with a more significant negative impact on quality of life.ConclusionThe study showed that diabetes generally had a negative impact on QoL and identified the demand for diabetes management programs tailored to patient needs and different patient groups, as well as health policies that put patients in the center of diabetes care.

Relationship between glycemic control and quality of life in elderly patients with type 2 diabetes in Alexandria University Hospitals

Introduction Diabetes mellitus type 2 (T2DM) is a chronic metabolic disease with a great impact on health status and quality of life (QoL) in terms of physical, social, and psychological well-being. The aim of the present study was to measure diabetes-dependent QoL and affecting factors in patients with T2DM. Patients and methods The study participants were men and women aged 65 years and older affected by T2DM recruited from the Geriatric Medicine Unit ward and from the outpatient Geriatric Medicine Clinic of the Alexandria University Hospital. ADDQoL and short form-12 health survey were used to assess QoL. Results Diabetes had a negative impact on QoL, especially in terms of the physical health according to ADDQoL and mild physical and moderate mental disability according to the short form-12 health survey. Multivariate analysis revealed that glycemic control was not a determinant of QoL. Conclusion The results of the study suggest that good glycemic control has a weak relationship with QoL.

Health Literacy and Quality of Life in Patients With Type 1 Diabetes Mellitus.

AimThe aim of this study was to investigate the relationship between health literacy (HL) and quality of life (QoL) in type 1 diabetes mellitus (DM) patients.MethodThis study was conducted between February 2020 and May 2020 at the University of Health Sciences Bursa Yuksek Ihtisas Training and Research Hospital, in Turkey. A total of 155 patients with type 1 DM between the ages of 18-65 were included in the study. QoL was evaluated with the Audit of Diabetes Dependent QoL questionnaire and HL was evaluated with the Newest Vital Sign (NVS) questionnaire and obtained results were compared.ResultsThe weighted impact score for the overall QoL scale was higher for patients who did not have complications than those with complications (p=0.004). Retinopathy and nephropathy were higher in the group with low HL (p=<0.001; p=0.032; p=0.012, respectively). The weighted impact score for the overall QoL scale was lower in married individuals (p=0.040) and it was higher for high school and above education levels than those with lower education levels (p=0.004). The sex life weighted impact score was higher in the group with DM less than 10 years (p=0.045).ConclusionPatients with high HL status are more adaptable to their physician's recommendations, less frequent complications will occur in these patients and the QoL of the patients will be better in the absence of complications.

Effect of Voluntary Participation on Mobile Health Care in Diabetes Management: Randomized Controlled Open-Label Trial.

BackgroundThe role of mobile health care (mHealth) in glycemic control has been investigated, but its impact on self-management skills and its psychological aspects have not been studied.ObjectiveWe evaluated the efficacy of mHealth-based diabetes self-management education and the effect of voluntary participation on its effects.MethodsThis study was a randomized controlled open-label trial conducted for 6 months at Kangbuk Samsung Hospital. Participants in the control group (n=31) maintained their previous diabetes management strategies. Participants in the intervention group (n=41) additionally received mHealth-based diabetes self-management education through a mobile app and regular individualized feedback from health care professionals. The primary outcome was change in glycated hemoglobin (HbA1c) level over 6 months between the 2 groups (intervention versus control) and within each group (at 6 months versus baseline). The secondary outcomes were changes in body mass index, blood pressure, lipid profile, and questionnaire scores (the Korean version of the Summary of Diabetes Self-Care Activities Questionnaire, an Audit of Diabetes Dependent Quality of Life, the Appraisal of Diabetes Scale, and Problem Areas in Diabetes) over 6 months between groups and within each group.ResultsA total of 66 participants completed this study. HbA1c (P=.04), total cholesterol level (P=.04), and Problem Areas in Diabetes scores (P=.02) significantly decreased; total diet (P=.03) and self-monitoring of blood glucose level scores (P=.01), based on the Summary of Diabetes Self-Care Activities Questionnaire, markedly increased within the intervention group. These significant changes were observed in self-motivated participants who were recruited voluntarily via advertisements.ConclusionsmHealth-based diabetes self-management education was effective at improving glycemic control and diabetes self-management skills and lowering diabetes-related distress in voluntary participants.Trial RegistrationClinicalTrials.gov NCT03468283; http://clinicaltrials.gov/ct2/show/NCT03468283

1629-P: Association of Patient-Reported Outcomes (PROs) Scores with Glycemic Target Achievement in Type 1 Diabetes (T1D) in the SAGE Study

T1D is a chronic disease affecting both physical and psychosocial health. SAGE was a multinational, cross-sectional observational study using data from medical records and interviews of people (N=3858) aged ≥26 years with T1D for ≥1 year. The association between the achievement of general (HbA1c &amp;lt;7 %) or individualized HbA1c targets and PRO scores was analyzed by multivariate logistic regression, adjusted for region and age group. The following PROs are reported: Hypoglycemia Fear Survey (HFS-II) worry subscore, Problem Areas in Diabetes (PAID), Insulin Treatment Satisfaction Questionnaire (ITSQ), Audit of Diabetes-Dependent Quality of Life (ADDQoL). Overall, 24.3% of people achieved the general HbA1c target; 20.9% achieved individualized targets (most common target, HbA1c 7 % to &amp;lt;7.5 %). Lower emotional distress (PAID score) and higher treatment satisfaction (all ITSQ scores except Lifestyle domain) were associated with achievement of general and individualized HbA1c targets (Table). Lower HFS-II worry score and higher ADDQoL total scores were associated with achievement of HbA1c general target, but neither was associated with achieving individualized HbA1c targets. In people with T1D, lower diabetes-related emotional distress and higher treatment satisfaction appear to be associated with achievement of both general and individualized HbA1c targets. Disclosure E.G. Wilmot: Advisory Panel; Self; Abbott, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic. Speaker’s Bureau; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Novo Nordisk Inc., Sanofi. F. Ampudia Blasco: None. L. Berard: Consultant; Self; Abbott, AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Becton, Dickinson and Company, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Montméd, Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Boehringer Ingelheim (Canada) Ltd. S. Brette: Other Relationship; Self; Sanofi. L.P. Calliari: Board Member; Self; Abbott, Medtronic, Novo Nordisk A/S, Sanofi. Speaker’s Bureau; Self; Lilly Diabetes. E. Fitts: Other Relationship; Self; N/A. K.L. Close: Other Relationship; Self; Abbott, Air Liquide, American Diabetes Association, AstraZeneca, Dexcom, Inc., Janssen Pharmaceuticals, Inc., JDRF, Leona M. and Harry B. Helmsley Charitable Trust, Lilly Diabetes, Merck &amp; Co., Inc. J.J. Gagliardino: None. F. Lauand: Employee; Self; Sanofi. A.L. Peters: Advisory Panel; Self; Abbott, Bigfoot Biomedical, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medscape, Novo Nordisk Inc., Sanofi US. Consultant; Self; Livongo Health. Research Support; Self; Dexcom, Inc., vTv Therapeutics. Other Relationship; Self; Livongo Health, Mellitus Health, Omada Health, Stability Healthcare, Whole Biome Inc. E. Renard: Board Member; Self; Abbott, Insulet Corporation, Novo Nordisk A/S, Roche Diabetes Care. Consultant; Self; Air Liquide, Eli Lilly and Company, Sanofi. Research Support; Self; Dexcom, Inc., Tandem Diabetes Care. A. Roborel de Climens: Employee; Self; Sanofi. J. Seufert: Research Support; Self; Sanofi. Speaker’s Bureau; Self; Sanofi.

1626-P: Differences in Patient-Reported Outcomes (PROs) by Age and Region in Adults with Type 1 Diabetes (T1D) in the SAGE Study

T1D is a chronic disease impacting patients’ lives and psychosocial health; we explored how this may vary by age and region. SAGE was a multinational, cross-sectional observational study using data from medical records and interviews of participants (N=3858) aged ≥26 years with T1D for ≥1 year. Results from PROs questionnaires (Hypoglycemia Fear Survey [HFS-II], Problem Areas in Diabetes [PAID], Insulin Treatment Satisfaction Questionnaire [ITSQ], Audit of Diabetes-Dependent Quality of Life [ADDQoL]) were analyzed by region (Asia [A], Eastern Europe [EE], Western Europe [WE], Latin America [LA], Middle East [ME]) and age group (26-&amp;lt;45; 45-&amp;lt;65; ≥65 years). HFS-II scores showed fear of hypoglycemia was lowest in A for all age groups (Table). HFS-II scores increased with age in EE and decreased with age in LA. PAID scores showed highest levels of emotional distress in ME for all age groups. ITSQ scores showed treatment satisfaction increased with age in WE, LA and ME, and was more stable in EE and A. ADDQoL total scores showed a small negative impact of T1D on quality of life, with the highest and lowest impact in EE and ME, respectively, across all ages. PROs scores indicated relatively low levels of diabetes-related impact and high treatment satisfaction. Age and regional differences may reflect variations in T1D control and management, as well as cultural and healthcare-system-related factors. Disclosure L. Berard: Consultant; Self; Abbott, AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Becton, Dickinson and Company, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Montméd, Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Boehringer Ingelheim (Canada) Ltd. F. Ampudia Blasco: None. S. Brette: Other Relationship; Self; Sanofi. D. Bruttomesso: Consultant; Self; Abbott, Eli Lilly and Company, Movi, Novo Nordisk, Roche Diagnostics, Sanofi. K.L. Close: Other Relationship; Self; Abbott, Air Liquide, American Diabetes Association, AstraZeneca, Dexcom, Inc., Janssen Pharmaceuticals, Inc., JDRF, Leona M. and Harry B. Helmsley Charitable Trust, Lilly Diabetes, Merck &amp; Co., Inc. H. Ikegami: None. D. Jurišic-Eržen: None. F. Lauand: Employee; Self; Sanofi. A.L. Peters: Advisory Panel; Self; Abbott, Bigfoot Biomedical, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medscape, Novo Nordisk Inc., Sanofi US. Consultant; Self; Livongo Health. Research Support; Self; Dexcom, Inc., vTv Therapeutics. Other Relationship; Self; Livongo Health, Mellitus Health, Omada Health, Stability Healthcare, Whole Biome Inc. V. Pilorget: Employee; Self; Sanofi. R. Balamurugan: None. E. Renard: Board Member; Self; Abbott, Insulet Corporation, Novo Nordisk A/S, Roche Diabetes Care. Consultant; Self; Air Liquide, Eli Lilly and Company, Sanofi. Research Support; Self; Dexcom, Inc., Tandem Diabetes Care. E.G. Wilmot: Advisory Panel; Self; Abbott, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic. Speaker’s Bureau; Self; Abbott, Eli Lilly and Company, Insulet Corporation, Novo Nordisk Inc., Sanofi. A. Roborel de Climens: Employee; Self; Sanofi. Funding Sanofi