Social consumption of alcohol in adolescents with Type 1 diabetes is associated with increased glucose lability, but not hypoglycaemia

Ismail, Dunia; Gebert, Rebecca; Vuillermin, Peter; Fraser, Lisa-Ann; McDonnell, Ciara M.; Donath, Susan; Cameron, F. J.

doi:10.1111/j.1464-5491.2006.01868.x

Cited by 37 publications

(51 citation statements)

References 8 publications

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“…The choice of the time difference, n, will depend on the clinical question being addressed. CONGA has been subsequently used in studies investigating both type 1 and type 2 diabetes [36][37][38]. CONGA has the benefits of being highly reproducible and able to be adjusted for varying time intervals depending on the specific issue being addressed.…”

Section: Continuous Overlapping Net Glycaemic Action (Conga)mentioning

confidence: 99%

Measuring Glycaemic Variation

Cameron

Donath²,

Baghurst³

2010

CDR

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The measurement of glycaemic variation (GV) is conceived to be of clinical significance in determining diabetes outcomes. The debate as to the importance of GV has been complicated by studies using various metrics of GV in qualitatively different datasets. The purpose of this review is to discuss the properties of 8 of the more commonly used metrics (M-value, MAGE, "J"-index, CONGA, BG rate of change, ADRR, Lability/HYPO score and GRADE). Comparable metrics that can be used to measure continuous glycaemic measurements (CGM) (SDBGL, "J"-index, MAGE, CONGA, GRADE) were then compared in assessing diabetic and non-diabetic datasets. In non-diabetic conditions there was very close correlation (correlation coefficients >0.92) between SDBGL, MAGE and CONGA, however under diabetic conditions the correlation coefficients of the GV metrics diminished significantly. The varying GV metrics have varying inherent properties depending upon the purpose for which they were designed and should not be seen as being interchangeable. Investigators therefore need to be clear about the nature of their enquiry of GV and choose an appropriate metric.

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Section: Continuous Overlapping Net Glycaemic Action (Conga)mentioning

confidence: 99%

Measuring Glycaemic Variation

Cameron

Donath²,

Baghurst³

2010

CDR

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“…Alcohol intake may also result in neglecting diabetes self-care – not measuring glycemia, omitting insulin doses and also involvement in risky behavior [68, 69]. These have an adverse influence on metabolic control and the course of disease, including glycemic instability and increased risk of DKA [70]. It is worth noting that moderate consumption of wine is not prohibited, and may have beneficial vascular effects in diabetes [71].…”

Section: Alcohol and Illicit Drugs Intakementioning

confidence: 99%

State of the art paper Influence of lifestyle on the course of type 1 diabetes mellitus

Piłaciński¹,

Zozulińska-Ziółkiewicz²

2014

aoms

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Type 1 diabetes (T1DM) is an autoimmune disease that requires insulin treatment from the time of diagnosis. Its clinical course depends on both genetic and environmental factors, and the lifestyle of a patient modulates their interaction. The evidence about the influence of lifestyle on the course of T1DM is increasing. In this paper, we present evidence on the relationship between lifestyle parameters and diabetes-related outcomes. We discuss the most commonly addressed factors associated with lifestyle, such as physical activity, nutrition and smoking, and those with sparse evidence in T1DM, such as socioeconomic status, sleep duration, psychological stress and illicit drugs intake.

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“…For example, one study found that moderately heavy alcohol consumption by adolescents with type 1 diabetes in a social setting (mean of 9 drinks for males, 6 for females—along with meals, sweetened mixers, and dancing) was associated with increased glycemic variation but not with hypoglycemia. 11 In adults with type 1 diabetes, consumption of alcohol has been linked with a greater number of hypoglycemic episodes the following day, 12,13 as well as impaired ability to recognize symptoms of hypoglycemia, a potentially serious outcome. 13 Results from these studies should be interpreted with caution, however, because of the small sample sizes (N = 10–17); more research is still needed to determine the patterns of alcohol use in adolescents with type 1 diabetes and the effects on self-management and blood glucose.…”

Section: Substance Usementioning

confidence: 99%

Risky Business

et al. 2011

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Purpose The purpose of this article is to review risk behaviors and their health consequences in adolescents with type 1 diabetes. The existing literature on common risk behaviors in adolescents is examined, with a focus on illicit drug use, alcohol use, smoking, unprotected sexual activity, and disordered eating behaviors. Conclusions A review of the literature highlights the lack of studies of risk behaviors in this population. Much of what is known comes from studies with adolescents in the general population or from studies of adults with type 1 diabetes. Known risk and protective factors for risk behaviors and health outcomes are noted. Based on these findings, suggestions are provided for diabetes educators and health care providers to assess for and prevent risk behaviors in adolescents with type 1 diabetes. Directions for future research in this population are indicated, including the need to develop and test standardized prevention programs.

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Social consumption of alcohol in adolescents with Type 1 diabetes is associated with increased glucose lability, but not hypoglycaemia

Abstract: In an uncontrolled, social context, moderately heavy alcohol consumption by adolescents with Type 1 diabetes appears to be associated with increased glycaemic variation, but not with low glucose levels.

Cited by 37 publications

References 8 publications

Measuring Glycaemic Variation

Measuring Glycaemic Variation

State of the art paper Influence of lifestyle on the course of type 1 diabetes mellitus

Risky Business

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