Use of telemedicine system to idebtify the increase in alcohol consumers among people with Type I diabetes during the COVID-19 pandemic.

Melo, Karla FS1,2; Feder, Cecilia KR1; Gueuvoghlanian-Silva, Barbara Y3; Almeida, Mariana P1; Cukier, Priscilla1; Calliari, LEP4, Silva, Maria ER1

Background and Aims

Covid-19 pandemic has changed the habits of people with diabetes, and social-distancing was associated with more time at home and individual distress. There are some reports about increasing in alcohol drinking among individuals with diabetes during the pandemic. Currently, many patients use telemedicine support systems. Glic® is a system widely used in Brazil, since 2012, with 50022 users with T1DM that insert food intake data, including alcohol. The aim of this study was to evaluate changes in alcohol consumption in individuals with T1DM, during COVID-19 pandemic, using a telemedicine support system (Glic®).


Data were obtained from Glic® database ( and were described using
absolute and relative frequencies for categorical variables. The percentage of alcohol consumers in users with T1DM and their relationship with the COVID-19 pandemic was assessed by adjusting a time series regression model, with ARIMA identification.

The adjustment considered the percentage of individuals who registered alcohol consumption, and the pandemic period from March to December 2020 was used as an explanatory variable, with the coefficient and p-value for each component of the model being presented. The analyzes were carried out with the R program and the “forecast” package. For all analyzes, the 5% significance level was adopted.


Glic® database contains 276815 records of alcohol consumption among patients with T1DM, for the period from January 2019 to December 2020, of which 274031 were identified as valid and non-null records. During this period, we recognize 20829 users who input at least one valid alcohol consumption record (Figure 1). In 2019 there were 95357 alcohol consumption records and 178674 ones in 2020, corresponding to an increase of 1,84 times in 2020.

There was an increase in percentage of alcohol consumers over time among Glic® users with T1DM.

The adjusted model for the data that better explained the variable behavior was a first-order moving averages model, considering as explanatory variables the month and the order of each month in the pandemic period. Regarding the explanatory variables related to the months, in each month was estimated an increase of 0.56% in the proportion of users who register alcohol consumption (95% CI: 0.31% to 0.81%; p <0.001 ), and in the pandemic months, it was estimated an additional increase of 0.58% in the proportion of users who register alcohol consumption (95% CI: 0.06% to 1.11%; p = 0.030), representing a monthly increase of 1.14% in the proportion of users who register alcohol consumption during the COVID-19 pandemic period.


There was an increase in the proportion of individuals with T1DM who registered alcohol consumption during the COVID-19 pandemic. Telemedicine system (Glic®) is a useful tool to detect behavioral changes in people with diabetes and might help the development of strategies to support and protect these individuals in specific


1. Sidor, A. and P. Rzymski, 2020. 12(6); 2. Yan, A.F., et alDiabetes Res Clin Pract, 2020. 167: p. 108350.; 3. D. G. Altman, Practical statistics for medical research, London: CRC press, 1991; 4. R Core Team. R: A language and environment for statistical computing. 2015. URL:; 5. Hyndman RJ, Khandakar Y. Automatic time series forecasting: the forecast package for R. Journal of Statistical Software. 2008; 26(3): p. 1-22.


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