Effect of Screen time on Glycaemic control of Type 2 Diabetes patients during COVID-19 Outbreak: A Survey based Study

  1. Sayak Roy
  2. Kingshuk Bhattacharjee

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Abstract

Introduction

Decreased workout during coronavirus disease 2019 (COVID-19) is a serious issue for the patients with type 2 diabetes (T2DM), since their glycaemic control is very much related to that. COVID-19 has posed a severe health issue that is playing havoc on the aged patients with existing comorbidities. Studies have shown mixed reports of social media on T2DM, with some showing positive results due to increased use of apps and adherence to lifestyle, while others have shown adiposity and glycaemic control related to hours spent on-screen time in children. Data on adult T2DM patients’ screen time activity and prevailing glycosylated haemoglobin (HbA1c), fasting blood sugar (FBS) and, post-prandial blood sugar (PPBS) is sparse.

Aim

To study the effect of screen-time spent on social media per day on glycaemic parameters of T2DM patients.

Materials and methods

Data was collected for T2DM patients giving informed written consent and meeting a set of pre-specified inclusion criteria. Through two rounds of surveys done from May 15 to June 26, the authors collected the answers to a set of questionnaires from a total of 344 patients sent via email. Due to the non-availability of data from a few patients, a total of 229 patients’ data were finally analyzed. SPSS software version V21 ® was used to perform Binary logistic regression for calculating the odds ratio (OR) of the categorical variables. The outcomes, looked for in the analysis, were poor control of glycaemic parameters like HbA1c (defined by >7%), FBS (defined by >150 mg/dL) and, PPBS (defined by >200 mg/dL) and the exposure variables were Screen time spent by the person per day for all the three glycaemic parameters and, doctor’s visit and, daily exercise for HbA1c outcome.

Results

A total of 173 patients had a screen time (henceforth, it means time spent on social media) of less than 2 hours/day in the study sample. Among the 173 patients, 73 (42.2%) had achieved HbA1c less than 7%, whereas the remaining 100 (57.8%) had HbA1c more than 7%. On the other hand, 56 patients had a screen time of more than 2 hours, of which 44 (72.73%) had HbA1c more than 7%. Among the 173 patients, only 89 (51.44%) had an FBS value of more than 150 mg/dL as compared to 46 (82.12%) with a screen time of more than 2 hours. Out of these 173 patients, only 43 (24.86%) had a PPBS value of more than 200 mg/dL as compared to 41 (73.21%) with a screen time of more than 2 hours. It was found that the odds of having a poor glycaemic control as per HbA1c, FBS and PPBS is 2.67 times higher (95%CI: 1.91-6.95), 4.34 times higher (95%CI: 1.52-4.76) and, 8.26 times higher (95%CI: 4.26-11.83) in the cohort with a screen time of more than 2 hours as compared to the cohort with a screen time of less than 2 hours, respectively.

Conclusion

There seems to be an increased risk of uncontrolled glycaemic indices with increased screen time and, decreased work out. This is a small study and the findings need to be corroborated with larger sample size.

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  1. Version published to 10.1101/2020.09.09.20188961v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.09.09.20188961: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: After contacting the selected group of patients telephonically, emails were sent for written informed consent form along with the survey questionnaires (figure 1).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.09.09.20188961v1 on medRxiv