Association of physical activity metrics with glucose variability in people with type 1 diabetes: A cross‐sectional study

Al Kandari, Jumana; Al Ozairi, Ebaa; Irshad, Mohammad; Varghese, Anisha; Gray, Stuart R.

doi:10.1002/ejsc.12062

Cited by 3 publications

(1 citation statement)

References 43 publications

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“… 12 , 13 Additionally, improved glucose variability has been observed in people with type 1 diabetes who spend a higher proportion of their day engaged in moderate to high-intensity physical activities. 14 Conversely, depression and anxiety have been shown to be associated with poorer glycemic control and long-term glycemic variability in people with type 1 diabetes. 15 , 16 Long-term sedentary behavior is as a potential risk factor for depressive symptoms, as reported in healthy adults in the US.…”

Section: Introductionmentioning

confidence: 99%

Association of Physical Activity and Sleep Metrics with Depression in People with Type 1 Diabetes

Al-Ozairi,

Irshad,

Alsaraf

et al. 2024

PRBM

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Objective This study aimed to investigate the association of physical activity and sleep metrics, measured via wrist-worn accelerometers, with depression in people with type 1 diabetes. Patients and Methods People with type 1 diabetes were recruited from the Dasman Diabetes Institute in Kuwait and were invited to wear a wrist-worn accelerometer device for 7 days. Mean physical activity (overall acceleration), inactivity, light activity, moderate activity, vigorous activity, the distribution of physical activity intensity (intensity gradient), sleep duration and sleep efficiency were quantified from the accelerometer data. The associations of these metrics with depression were investigated using multiple linear regression. Results A total of 551 people with type 1 diabetes (age 33.1 (9.5) years) were included. Overall physical activity (B = −0.09, CI = −0.14 to –0.04), moderate intensity activity (B = −0.02, CI = −0.02 to −0.01), vigorous intensity activity (B = −0.16, CI = −0.27 to −0.05), and the intensity gradient (B = −2.11, CI = −3.51 to −0.72) were negatively associated with depression score (p < 0.01) and these associations remain significant even after adjustment for age, sex, diabetes duration, and BMI. However, sleep duration and efficiency were not associated with depression. After mutual adjustment overall physical activity (B = −0.07, CI = −0.12 to −0.01), but not the intensity gradient (B = −0.90, CI = −2.47 to 0.68), remained associated with depression. Conclusion Overall, moderate and vigorous physical activity, and the intensity gradient were associated with lower symptoms of depression. Overall physical activity, rather than the distribution of activity intensity, appears more important in depression. This information can help guide physical activity interventions to improve depression in people with type 1 diabetes.

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Section: Introductionmentioning

confidence: 99%

Association of Physical Activity and Sleep Metrics with Depression in People with Type 1 Diabetes

Al-Ozairi,

Irshad,

Alsaraf

et al. 2024

PRBM

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Unveiling the Spectrum of Glucose Variability: A Novel Perspective on FreeStyle Libre Monitoring Data

Heald,

Stedman,

Warner-Levy

et al. 2024

Diabetes Ther

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Introduction Since the introduction of insulin therapy, it has become apparent that type 1 diabetes (T1D) is accompanied by long-term microvascular and macrovascular complications. In the context of the many benefits of continuous glucose monitoring (CGM), there remain opportunities to study the large amount of data now available in order to maximise its potential in the endeavour to reduce the occurrence of diabetes tissue complications in the longer term . Methods Continuous glucose monitoring values were downloaded for 89 type 1 diabetes mellitus (T1D) individuals for up to 18 months from 2021 to 2023. Data for patient demographics was also taken from the patient record which included Sex, Date of Birth, and Date of Diagnosis. The recorded laboratory glycated haemoglobin (HbA1c) test results were also recorded. The glucose management index (GMI) was calculated from average glucose readings for 18 months using the formula GMI (%) = (0.82 − (Average glucose/100)). This was then adjusted to give GMI (mmol/mol) = 10.929 * (GMI (%) − 2.15). Average Glucose Fluctuation (AGF) was calculated by adding up the total absolute change value between all recorded results over 18 months and dividing by the number of results minus one. The % Above Critical Threshold (ACT) was calculated by summing the total number of occurrences for each result value. A cumulative 95% limit was then applied to identify the glucose value that only 5% of results exceeded in the overall population. Using this value, we estimated the percentage of total tests that were above the Critical Threshold (ACT). Results The mean age of the participants was 42.6 years, and the mean duration of T1D was 18.4 years. A total of 3.22 million readings were analysed, yielding an average blood glucose level of 10.3 mmol/l and a GMI of 57.2 mmol/mol. There was a strong correlation between GMI and measured HbA1c ( r 2 = 0.82). However, there were patients who had an above-critical threshold (ACT) of 4–10% at a GMI of 60 mmol/mol or less. The percentage average value at the time of day (%AVTD) was applied to all blood glucose readings at each 15-min interval throughout the day, averaged over 18 months. The %AVTD of GMI (overall average 57.2 mmol/mol) increased after midday, dipped at 18:00, and peaked at 22:00. The %AVTD of AGF (overall average 0.60 mmol/l) showed higher change rates after 09:00 declining at the end of the day. The %AVTD of ACT peaked at 22:00, with those having the highest %ACT showing an additional peak at 15:00. Conclusions We have shown here that the percentage glucose results above 18 mmol/l (top 5% of distribution) increased exponentially above 54 mmol/mol HbA1c. The %AVTD is introduced as a useful measure. Our data indicate that over the 24-h period, improvement in metabolic control could be focussed on the afternoon and evening, when there are higher-than-average levels...

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Prevalence and predictors of diabetes distress and depression in people with type 1 diabetes

AlOzairi,

Irshad,

AlKandari

et al. 2024

Front. Psychiatry

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BackgroundPeople living with diabetes often encounter psychosocial challenges, including diabetes distress and depression. Despite this, little research has focused on the co-occurrence of these conditions. This study aimed to explore the prevalence of depressive symptoms and diabetes distress in people with type 1 diabetes in Kuwait and to identify clinical and demographic factors associated with these conditions.MethodsA total of 832 people with type 1 diabetes (females: 54.1%, mean age: 29 ± 8.5 years), were invited to participate in Dose Adjustment for Normal Eating (DAFNE) course. Diabetes distress was measured using the Problem Areas in Diabetes (PAID) scale and depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9). Depressive symptoms were defined as PHQ-9 scores ≥10. Data on biomedical outcomes, lifestyle factors, and sociodemographic information were collected.ResultsThe prevalence rates of diabetes distress and depressive symptoms were 27.8% and 38.3%, respectively. Notably, 19.6% of people experienced both conditions. In the regression analysis, PAID scale and PHQ-9 scores were significantly associated, patients with higher score on depressive symptoms scale were more likely to suffer diabetes distress (B= 2.65, p < 0.001). Female sex (odds ratio [OR]= 2.2, 95% CI= 1.5, 3.2), higher hemoglobin A1c levels (OR= 1.6, 95% CI= 1.0, 2.5), obesity (OR= 1.7, 95% CI= 1.1, 2.8), inactivity (OR= 2.4, 95% CI= 1.6, 3.6), microvascular complications (OR= 2.8, 95% CI= 1.5, 5.4), and lipohypertrophy (OR= 1.7, 95% CI= 1.1, 2.5) were associated with greater odds for the co-occurrence of diabetes distress and depressive symptoms (p< 0.05 for all).ConclusionThe majority of people with type 1 diabetes in Kuwait experience both diabetes distress and depressive symptoms. The strong correlation between diabetes distress and depressive symptoms suggests mutual predictability. The co-occurrence of both symptoms is associated with many sociodemographic and clinical factors.

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Association of physical activity metrics with glucose variability in people with type 1 diabetes: A cross‐sectional study

Cited by 3 publications

References 43 publications

Association of Physical Activity and Sleep Metrics with Depression in People with Type 1 Diabetes

Association of Physical Activity and Sleep Metrics with Depression in People with Type 1 Diabetes

Unveiling the Spectrum of Glucose Variability: A Novel Perspective on FreeStyle Libre Monitoring Data

Prevalence and predictors of diabetes distress and depression in people with type 1 diabetes

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