Encouraging Physical Activity in Patients With Diabetes Through Automatic Personalized Feedback via Reinforcement Learning Improves Glycemic Control: Table 1

Background: The prevalence of diabetes has been rising sharply since 1980, reaching 422 million cases worldwide in 2014. Physical activity and handgrip strength may be associated with good glycaemic control among patients with diabetes Objective: We tested the association between handgrip strength and glycemic control in type 2 diabetes patients, from National Health and Nutritional Examination Survey NHANES 2011-2014 and the contribution of the study covariates to this association. Hypothesis: Muscle strength is positively associated with glycemic control in type two diabetes. Methodology: This cross-sectional study examined the association between handgrip strength and glycaemic control among patients with diabetes. Data on 1058 participants aged 40 and older were collected from the NHANES. Muscle strength was assessed using a handgrip dynamometer, and blood samples were obtained to observe the glycaemic control values. Height, body weight, physical activity, insulin use, smoking status, alcohol use, participant demographics, and income-to-poverty ratio were all considered in the study. Results: logistic regression analysis was used to assess the association between handgrip strength and poor glycaemic control among participants with diabetes. Three models were used, each model adjusted to include different variables. OR values revealed no association between handgrip strength and glycaemic control. However, model 2, which was adjusted for sedentary activity, income-topoverty ratio, education, and smoking, shows a trend towards an association. Patients in quartile 4 of handgrip had 0.59 odds of poor glycaemic control, OR = 0.59 (95% CI: 0.34–1.02). However, in model 3 this effect was diluted when further adjusted for insulin use, OR = 0.81 (95% CI: 0.47– 1.38). Further analysis was performed to examine the mean decline in handgrip strength among non-insulin and insulin users. Non-insulin users, both men and women, have higher handgrip strength as compared to insulin users. Conclusion: There was no association found between handgrip and glycaemic control among patients with diabetes.

Download Full-text

Empowering Patients for Healthy Nutrition, Physical Activity, and Self-Care Using the Diabetes Score Questionnaire

Dubai Diabetes and Endocrinology Journal ◽

10.1159/000519225 ◽

2021 ◽

Vol 27 (4) ◽

pp. 131-136

Author(s):

Muhammad Jawad Hashim ◽

Halla Mustafa

Keyword(s):

Physical Activity ◽

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Glycemic Control ◽

Lifestyle Change ◽

Lifestyle Factors ◽

Health Care Center ◽

Healthy Nutrition ◽

Patients With Diabetes

Objectives: Lifestyle factors such as nutrition and physical activity play an important role in the management of diabetes mellitus. Unfortunately, adherence to lifestyle change remains low among patients with diabetes. The aim of this study was to evaluate the effectiveness of the Diabetes Score questionnaire in a clinical setting. Methods: The Diabetes Score is a 10-item shared decision-making tool designed to empower lifestyle change in individuals with diabetes. It yields an intuitive score from 0 to 100 based on a patient’s adherence to lifestyle recommendations. An observational study was conducted at an ambulatory health care center. After obtaining written informed consent, adult patients with type 2 diabetes mellitus were interviewed by a trained researcher using the Diabetes Score questionnaire. Patients’ Diabetes Score values were analyzed in reference to their glycemic control and other clinical and demographic factors. Results: A total of 60 individuals with type 2 diabetes participated in the study. The mean age was 56 years (minimum 43 years, maximum 70 years) with 60% being males. Higher Diabetes Scores correlated with better glycemic control (hemoglobin A1C; r = −0.23, p = 0.044) indicating the effect of lifestyle factors such as healthy nutrition, smaller portion sizes, active lifestyle, and aerobic exercise. The questionnaire showed internal consistency (alpha 0.66), construct validity, and high patient satisfaction (98%). Conclusion: Diabetes Score, a behavioral lifestyle questionnaire, correlates with glycemic control in type 2 diabetes. Diabetes Score can be used in clinical settings for measuring, discussing, and setting targets for lifestyle change among patients with diabetes.

Download Full-text

Effectiveness of a Multicomponent Intervention in Primary Care That Addresses Patients with Diabetes Mellitus with Two or More Unhealthy Habits, Such as Diet, Physical Activity or Smoking: Multicenter Randomized Cluster Trial (EIRA Study)

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18115788 ◽

2021 ◽

Vol 18 (11) ◽

pp. 5788

Author(s):

Francisco Represas-Carrera ◽

Sabela Couso-Viana ◽

Fátima Méndez-López ◽

Bárbara Masluk ◽

Rosa Magallón-Botaya ◽

...

Keyword(s):

Physical Activity ◽

Diabetes Mellitus ◽

Glycemic Control ◽

Mediterranean Diet ◽

Sedentary Lifestyle ◽

Mean Difference ◽

Individual Group ◽

Patients With Diabetes ◽

Life Habits

Introduction: We evaluated the effectiveness of an individual, group and community intervention to improve the glycemic control of patients with diabetes mellitus aged 45–75 years with two or three unhealthy life habits. As secondary endpoints, we evaluated the inverventions’ effectiveness on adhering to Mediterranean diet, physical activity, sedentary lifestyle, smoking and quality of life. Method: A randomized clinical cluster (health centers) trial with two parallel groups in Spain from January 2016 to December 2019 was used. Patients with diabetes mellitus aged 45–75 years with two unhealthy life habits or more (smoking, not adhering to Mediterranean diet or little physical activity) participated. Centers were randomly assigned. The sample size was estimated to be 420 people for the main outcome variable. Educational intervention was done to improve adherence to Mediterranean diet, physical activity and smoking cessation by individual, group and community interventions for 12 months. Controls received the usual health care. The outcome variables were: HbA1c (main), the Mediterranean diet adherence score (MEDAS), the international diet quality index (DQI-I), the international physical activity questionnaire (IPAQ), sedentary lifestyle, smoking ≥1 cigarette/day and the EuroQuol questionnaire (EVA-EuroQol5D5L). Results: In total, 13 control centers (n = 356) and 12 intervention centers (n = 338) were included with similar baseline conditions. An analysis for intention-to-treat was done by applying multilevel mixed models fitted by basal values and the health center: the HbA1c adjusted mean difference = −0.09 (95% CI: −0.29–0.10), the DQI-I adjusted mean difference = 0.25 (95% CI: −0.32–0.82), the MEDAS adjusted mean difference = 0.45 (95% CI: 0.01–0.89), moderate/high physical activity OR = 1.09 (95% CI: 0.64–1.86), not living a sedentary lifestyle OR = 0.97 (95% CI: 0.55–1.73), no smoking OR = 0.61 (95% CI: 0.54–1.06), EVA adjusted mean difference = −1.26 (95% CI: −4.98–2.45). Conclusions: No statistically significant changes were found for either glycemic control or physical activity, sedentary lifestyle, smoking and quality of life. The multicomponent individual, group and community interventions only showed a statistically significant improvement in adhering to Mediterranean diet. Such innovative interventions need further research to demonstrate their effectiveness in patients with poor glycemic control.

Download Full-text

Sleeping Duration, Napping and Snoring in Association with Diabetes Control among Patients with Diabetes in Qatar

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084017 ◽

2021 ◽

Vol 18 (8) ◽

pp. 4017

Author(s):

Hiba Bawadi ◽

Asma Al Sada ◽

Noof Al Mansoori ◽

Sharifa Al Mannai ◽

Aya Hamdan ◽

...

Keyword(s):

Physical Activity ◽

Glycemic Control ◽

Sleep Duration ◽

Vegetable Intake ◽

Activity Level ◽

Poor Glycemic Control ◽

Age And Gender ◽

Increased Risk ◽

Patients With Diabetes ◽

And Gender

Background: Poor glycemic control is associated with chronic life-threatening complications. Several studies have revealed that sleep status is associated with glycemic control. Aim: to examine the association between sleep duration, quality and glycemic control among adults with diabetes. Methods: Data on 2500 participants aged 18–60 years were collected from the Qatar Biobank (QBB). Sleep duration and quality were assessed by a self-completed health and lifestyle questionnaire, and glycemic control was assessed using HbA1c. Logistic regression was used to assess the association between sleep duration, napping, snoring and poor glycemic control. Results: After adjusting for age and gender, sleep duration was not associated with poor glycemic control. Lack of association persisted after controlling for smoking, physical activity, education, BMI, fruit and vegetable intake, insulin and medication use. However, sleeping for long hours at night (≥8 h) had a trend in increasing the risk of poor glycemic control (OR = 1.28; 95% CI: 0.94–1.74). Napping was positively associated with poor glycemic control. After adjusting for age and gender, patients who reported “sometimes, frequently, or always” napping had more than 30% increased risk of poor control as compared to patients who reported “never/rarely” napping. Snoring was not associated with poor glycemic control among the study sample when adjusted for age and gender (p = 0.61). Other factors were found to be associated with a better glycemic control such as female, high educational and high physical activity level. Conclusions: our results suggest that napping may be an independent risk factor for a poor glycemic control in diabetes; further investigations are required.

Download Full-text

Encouraging Physical Activity in Patients With Diabetes: Intervention Using a Reinforcement Learning System

Journal of Medical Internet Research ◽

10.2196/jmir.7994 ◽

2017 ◽

Vol 19 (10) ◽

pp. e338 ◽

Cited By ~ 37

Author(s):

Elad Yom-Tov ◽

Guy Feraru ◽

Mark Kozdoba ◽

Shie Mannor ◽

Moshe Tennenholtz ◽

...

Keyword(s):

Physical Activity ◽

Reinforcement Learning ◽

Learning System ◽

Patients With Diabetes ◽

Diabetes Intervention

Download Full-text

Glycemic Control and its Predictors among Diabetic Patients Attending a Tertiary Hospital in Nigeria: A Retrospective Observational Study

Journal of Biomedical Analytics ◽

10.30577/jba.v3i1.42 ◽

2020 ◽

Vol 3 (1) ◽

pp. 13-25

Author(s):

Yau Adamu ◽

Khalid M. Garba ◽

Shamsudeen YAU ◽

Jamilu Ya'u

Keyword(s):

Physical Activity ◽

Glycemic Control ◽

Care Facility ◽

Health Care Facility ◽

Tertiary Hospital ◽

Tight Glycemic Control ◽

Diabetic Patients ◽

Good Glycemic Control ◽

Lower Odds ◽

Patients With Diabetes

The prevalence of diabetes and its associated complications have continued to increase globally. Tight glycemic control has been one of the effective ways towards the management of diabetes and its complications. This study was conducted to investigate independent predictors of glycemic levels among patients with diabetes attending a diabetic clinic of a tertiary health care facility. More than half (54.2%) of the 216 participants had good glycemic control. Participants with Body Mass Index (BMI) more than 25 had 79% lower odds of having controlled glycemic levels (95% CI; 0.095, 0.479), compared to those with BMI$<=25. Patients on combination therapy have a significantly higher odds of having good glycemic control compared to those on monotherapy [AOR 3.43 (1.615, 7.302)]. Other identified significant predictors of glycemic control include multiple complications, retinopathy, ethnicity, and self-reported physical activity (p<0.05). Our findings demonstrated that ethnicity, BMI, physical activity, retinopathy, and having more than one complication were independently associated with good glycemic control levels.

Download Full-text