|Year : 2022 | Volume
| Issue : 3 | Page : 11-17
Effect of COVID-19 lockdown on glycemic status of patients with T2DM and effects of various factors involved
Yogesh Kumar, Amit Nachankar
Department of Endocrinology, Command Hospital, Lucknow, Uttar Pradesh, India
|Date of Submission||17-May-2021|
|Date of Decision||11-Sep-2021|
|Date of Acceptance||04-Oct-2021|
|Date of Web Publication||01-Apr-2022|
Lt Col (Dr) Amit Nachankar
Department of Endocrinology, Command Hospital, Lucknow - 226 002, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Background: The recent coronavirus disease 2019 lockdowns forced people to stay indoors, resulting in lower physical activity, and change in dietary patterns, impacting glycemic control in the diabetic population. We aimed to assess the impact of the 3-month lockdown on glycemic control among outpatients with type 2 diabetes (T2DM) being treated at our hospital. Study Design: This retrospective study included data of outpatients aged ≥30 years with preexisting T2DM, regularly attending the clinic during the prelockdown period and who came for follow-up postlockdown. The primary outcome measures were change in glycated hemoglobin (HbA1c), fasting blood glucose sugar (FBG), and postprandial blood sugar (PPBG) compared to the last value before the lockdown. Results: A total of 200 (male: female – 83:117) patients with a mean (standard deviation [SD]) age of 58.0 (10.8) years were included. The mean (SD) interval between the pre- and post-lockdown visit was 3.9 (0.9) months, and 58.5% of the patients were compliant with the medication. The mean HbA1c levels increased significantly by 1.1 (P = 0.000), FBG by 21.9 mg/dL (P = 0.000), PPBG by 28.0 mg/dL (P = 0.000), and weight by 1.6 kg (P = 0.000), from pre- to post-lockdown visit. The patients noncompliant to therapy had a significantly higher increase in glycemic parameters. The results showed a significant correlation between the interval of follow-up and treatment compliance with increase in glycemic parameters and weight. Conclusion: The results of this study revealed that there was a negative impact of lockdown on glycemic control in T2DM patients, highlighting the need for telehealth strategies to ensure the well-being of diabetic patients during such calamities.
Keywords: Coronavirus disease 2019, diabetes, glycemic control, lockdown, type 2 diabetes
|How to cite this article:|
Kumar Y, Nachankar A. Effect of COVID-19 lockdown on glycemic status of patients with T2DM and effects of various factors involved. J Mar Med Soc 2022;24, Suppl S1:11-7
| Introduction|| |
A healthy lifestyle is important for glycemic control in Type 2 diabetes (T2DM). A large amount of evidence from different studies supports the long-term beneficial effects of regular physical activity and weight loss in controlling the metabolic parameters and limiting the complications associated with T2DM.,
Since January 2020, the world has been witnessing the rapidly evolving outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory distress syndrome-coronavirus-2. An unprecedented health-care crisis, COVID-19, was declared a global pandemic by the World Health Organization on March 11, 2020., To contain the spread of COVID-19, governments across the world, including India, imposed a series of phased lockdowns. In India, the lockdown was announced on March 21, 2020, and continued until May 4, 2020, with phased relaxations thereafter.
During the lockdown, medical services were limited to emergencies. While this was vital to control the spread of the virus, it adversely impacted people suffering from other chronic diseases. In diabetics, a likelihood of worsening hyperglycemia, and an increase in diabetes-related complications, was reported. During the lockdown, people were forced to stay indoors, leading to lower physical activity, change in dietary patterns, and impact on mental health. People reported increased anxiety, which can lead to emotional eating and increased consumption of the so-called comfort food, which is mainly rich in simple carbohydrates. Many government-aided secondary and tertiary facilities were converted to COVID-19 care centers, affecting the regular outpatient flow, leading to a loss of follow-up and discontinuation of medication among patients with chronic diseases. Moreover, many senior doctors closed down their private clinics out of fear of contracting the virus.,
The importance of diabetic control during the lockdown is significant not only to prevent the direct complications of diabetes but also to reduce the risk of mortality among people with diabetes affected by COVID-19. In previous disease epidemics, a greater risk of viral infection was reported in people with diabetes. In the case of COVID-19, although the rate of infection among people with diabetes is not higher, it has been observed that diabetes is more common among those with severe COVID-19., Data from two hospitals in Wuhan including 1561 patients with COVID-19 showed that those with diabetes (9·8%) were more likely to require admission to an intensive care unit or had a high rate of mortality., Similarly, in a British cohort of 5693 patients hospitalized due to COVID-19, the risk of death was higher in those with uncontrolled diabetes (hazard ratio 2·36, 95% CI 2·18–2·56).
A simulation model was created using glycemic data from previous disasters (considered as similar in impact to the current lockdown). The data of baseline glycosylated hemoglobin (HbA1c) and diabetes-related complications were retrieved from an India-specific database. The predicted increase in HbA1c from baseline at the end of 30 days and 45 days of lockdown was projected to be 2.26% and 3.68%, respectively. In contrast, a recent report from Italy suggests that quarantine and lockdown might be beneficial for the short-term management of Type 1 diabetes (T1DM). However, studies conducted in India about the impact of the COVID-19 lockdown on glycemic control among diabetics, have reported contradictory outcomes, with studies reporting both beneficial and negative, impact of the pandemic on glycemic control. This retrospective study aimed to assess the impact of the 3-month lockdown period on weight and glycemic control among outpatients with T2DM being treated at our hospital.
Study design and population
This single-center, retrospective, observational study was conducted at the Department of Endocrinology, at a tertiary care hospital, in Lucknow, Uttar Pradesh, India. Data of outpatients with preexisting T2DM aged above 30 years, regularly attending the clinic during the prelockdown period, and who came for follow-up in the post lockdown period (up to June 30, 2020), were considered for this retrospective analysis.
Data were collected from the patients' medical records and included demographic details; duration of T2DM; anti-diabetic treatments; comorbid diseases; the interval between pre- and postlockdown visits; and pre- and postlockdown values for fasting blood glucose (FBG) and postprandial blood glucose (PPBG), HbA1c, and body weight.
Blood glucose estimation was done by using the venous blood sample glucose oxidase method for FBG and 2 h postbreakfast for PPBG, in the biochemistry laboratory. HbA1c was estimated using venous blood sample in ethylenediaminetetraacetic acid vacutainer by HPLC method as per the National Diabetes Data Group criteria standardized to Diabetes Control and Complications Trial assay. Treatment compliance was assessed by verbal questioning regarding regular drug therapy and access or availability of medicines during the COVID lockdown. Physical exercise and diet were assessed by verbal questioning regarding regular exercise and diet compliance.
The primary outcome measures were change in HbA1c, FBG, and PPBG and the secondary outcome measure was a change in weight of the patient, compared to the last observed value before the lockdown period. In addition to this, impact of factors such as patients' compliance to treatment (due to the availability of antidiabetic drugs), diet, exercise, and accessibility to consultation to modify treatment was also assessed.
The study was conducted in conformity with the principles of the Declaration of Helsinki, International Council for Harmonization-Good Clinical Practices (ICH-GCP) guidelines, and Indian Council of Medical Research, Indian GCP guidelines. The process of data analysis was initiated after approval from the ethics committee. As this was a retrospective study, informed consent was not required. Patient confidentiality was maintained during the data entry and analysis process.
Quantitative (continuous) variables were presented as descriptive statistics. The pre- and postlockdown glycemic variables were compared using a paired t-test at a 5% level of significance and the corresponding P value was presented. The correlation between change in glycemic control (FBG, PPBG, and HbA1c) with the change in weight, the interval between visits, treatment compliance, and duration of diabetes was also analyzed. As this was a retrospective data analysis, no sample size computation was done, and data of all the patients who attended the clinic during the prelockdown period and came for follow-up in the post lockdown period (up to June 30, 2020) were considered for this retrospective analysis. Data were analyzed using SPSS® statistics software, version 23.0 (IBM Corp., Armonk, NY, USA).
| Results|| |
A total of 200 (male: female – 83:117) patients with a mean (standard deviation [SD]) age of 58.0 (10.8) years were considered for this retrospective study. The mean (SD) interval between the pre- and postlockdown visits was 3.9 (0.9) months, and the majority of the patients (117 [58.5%]) were compliant with the treatment prescribed. The most commonly associated comorbidity was hypertension and chronic kidney disease, observed in 30.5% and 11.5% of the patients, respectively. The demographic and baseline characteristics of patients are summarized in [Table 1].
The mean change in glycemic variables and weight pre- to postlockdown are presented in [Table 2]. Compared to the prelockdown mean (SD) HbA1c levels of 8.1 (2.0), the postlockdown HbA1c levels increased significantly by 1.1 (P = 0.000). The mean FBG and PPBG levels also increased significantly by 21.9 mg/dL (P = 0.000) and by 28.0 mg/dL (P = 0.000) postlockdown, respectively, compared to the prelockdown mean (SD) scores of 162.7 (70.0) mg/dL and 234.0 (89.7) mg/dL, respectively. Similarly, the mean weight increased significantly by 1.6 kg (P = 0.000), postlockdown, compared to the prelockdown mean (SD) weight of 66.9 (7.1) kg.
|Table 2: Pre- and postlockdown mean glycemic variables and weight – overall|
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Glycemic parameters and weight from the prelockdown period increased significantly in both male (n = 83) and female (n = 117) patients (both P < 0.001). However, the overall comparison between sexes showed that the postlockdown change in HbA1c levels was comparable between the sexes (P = 0.211). Similarly, no significant differences between the sexes were observed with respect to change in FBG (P = 0.925) and PPBG (P = 0.622) [Table 3]. The change in weight from prelockdown to the postlockdown period also did not differ between male and female patients (P = 0.918) [Table 3].
|Table 3: Mean change in glycemic variables and weight – on the basis of gender and therapy prescribed|
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Similarly, the glycemic parameters and weight increased significantly in patients on oral antidiabetics (OADs) (n = 102) and insulin (with or without OADs) (n = 98) therapy (both P < 0.001). However, the overall comparison between the two groups showed that the postlockdown changes in HbA1c (P = 0.400), FBG (P = 0.224), PPBG (P = 0.268), and weight (P = 0.735) were comparable between the groups [Table 3].
Further assessment of the change in weight and glycemic variables from pre- to postockdown period based on the patient's adherence to the treatment prescribed, indicated that patients' noncompliant to therapy (n = 87) had a significantly higher increase in glycemic parameters and weight than the patients compliant to therapy prescribed (n = 117).
The postlockdown mean HbA1c level also increased significantly (P = 0.000) by 1.5 and by 0.8 in patients noncompliant and compliant to therapy, respectively. The increase in HbA1c levels was significantly more (0.7 [95% CI: 0.4–1.1; P = 0.000]) in patients noncompliant to therapy [Figure 1]. The mean postlockdown weight also increased significantly (P = 0.000) by 2.0 kg and by 1.5 kg in patients noncompliant and compliant to therapy, respectively. The increase in weight was significantly more (0.5 kg [95% CI: 0.2–0.9; P = 0.002]) in patients noncompliant to therapy [Figure 1].
|Figure 1: Comparative assessment of change in weight and glycated hemoglobin levels between patients compliant and noncompliant to therapy prescribed|
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Similarly, the postlockdown FBG levels increased significantly (P = 0.000) by 38.3 mg/dL and by 10.5 mg/dL in patients noncompliant and compliant to therapy, respectively. The increase in postlockdown FBG levels was significantly higher (27.8 [95% CI: 16.2–35.9; P = 0.000]) in patients noncompliant to therapy [Figure 2]. The postlockdown PPBG levels increased significantly (P = 0.000) by 50.4 mg/dL in patients noncompliant and insignificantly (P = 0.081) by 12.1 mg/dL in patients compliant to therapy; the increase in PPBG was significantly more (38.3 [95% CI: 23.2–53.5; P = 0.000]) in patients noncompliant to therapy [Figure 2].
|Figure 2: Comparative assessment of change in fasting blood glucose and postprandial blood sugar levels between patients compliant and noncompliant to therapy prescribed|
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The results of this retrospective analysis revealed a positive and significant correlation between change in weight with the change in FBG (r = 0.173, n = 199, P = 0.015), PPBG (r = 0.188, n = 200, P = 0.008), and change in HbA1c (r = 0.362, n = 200, P = 0.000). Similarly, the duration of interval between visits (months) significantly correlated to the change in FBG (r = 0.140, n = 199, P = 0.049) and PPBG (r = 0.145, n = 200, P = 0.041), but not with HbA1c (r = 0.068, n = 200, P = 0.339).
In addition, treatment compliance (noncompliant and compliant to therapy prescribed) was inversely and significantly correlated to the change in FBG (r = −0.276, n = 199, P = 0.000), PPBG (r = −0.317, n = 200, P = 0.000), and HbA1c (r = −0.253, n = 200, P = 0.000). However, we did not find a significant correlation between the duration of diabetes and change in FBG (r = 0.102, n = 197, P = 0.153), though the duration of diabetes showed a significant correlation with the change in PPBG (r = 0.158, n = 198, P = 0.026), and HbA1c (r = 0.180, n = 198, P = 0.011).
| Discussion|| |
Our study found that during an average interval of 3.9 months between the pre and postlockdown visits, only 58.5% of the patients were compliant with the medication. All glycemic parameters including HbA1c, FBG, PPBG, and weight significantly increased compared to the prelockdown levels. The changes were similar in both sexes and also between those on OADs or insulin (with or without OADs).
The possible cause of the increase in HbA1c, FBG, PPBG, and weight in our retrospective analysis can be attributed to multifactorial etiologies such as lack of required exercise, noncompliance to diet, partial or complete noncompliance to treatment due to nonavailability of weight-lowering antidiabetic drugs, nonaccessibility consultation to modify treatment, and stress of the pandemic due to lockdown restrictions.
Chronic diseases such as T1DM and T2DM require regular and long-term follow-up for medical care., However, due to the COVID-19-related social distancing norms, medical care to these patients has been greatly hampered. Follow-up nonattendance correlates with poor control of the chronic illness and reduced clinical effectiveness. As seen from the results of our retrospective study, the length of the interval between the visits (months) was significantly correlated to an increase in FBG and PPBG.
Treatment noncompliance in T2DM patients is documented and is associated with poor glycemic control and increased morbidity and mortality. The effect of the COVID-19 pandemic on treatment compliance in patients with T2DM remains unclear. Ghosal et al. in a predictive model established a direct relationship between the duration of lockdown and nonadherence to treatment and its association with uncontrolled glycemia. The results from our retrospective analysis also revealed that patients noncompliant to therapy had a significantly higher increase in glycemic parameters and weight compared to patients compliant to therapy. In addition, our results also illustrated that treatment noncompliance was significantly associated with an increase in FBG, PPBG, and HbA1c.
During the COVID-19 pandemic, many countries set up dedicated helplines for those experiencing mental health issues, including the diabetic population.,, However, the majority of people with noncommunicable diseases reside in low- to middle-income countries, where these technologies might not be widely available or practical. Even before the pandemic, health-care systems in low- and middle-income countries were challenged in providing high-quality, affordable, and universally accessible care. Moreover, the increased likelihood of being infected at hospitals forced most patients to avoid visiting health facilities for physician consultations during the pandemic. Individuals with diabetes are not always able to self-cafe and modify drug doses. Complications arising from poorly managed blood glucose such as diabetic ketoacidosis increase the risk for morbidity and mortality.
A recently published review of 46 studies aimed to analyze the evidence on the impact of telemedicine solutions on clinical outcomes of HbA1c and other lifestyle diseases. It included patients with T2DM (n = 24,000) and T1DM (n = 2052). Different modalities of telemedicine were studied. These included digital self-management, mobile health, social network services, and teleconsultation. Telemedicine significantly reduced HbA1c in patients with T2DM. Relevant digital self-management interventions showed clinically significant reductions in HbA1c if they provided remote access to usual care by SMS-based feedback and potential risk reducing interventions using a structured display with provision of medication and lifestyle modification management. In the UK, a group of diabetologists and other clinicians have set up a social media account to help alleviate patients' fears around COVID-19 and provide them with “a secure base” of information.
Khare and Jindal conducted a study in Central India involving 143 diabetic patients with a mean age of 54 years and good glycemic control in the 3 months before the pandemic. The duration of the study was 3 weeks during the first phase of the lockdown. The subjects had been advised self-monitoring of blood glucose (SMBG) for a minimum of 2 readings which included FBG and PPBG, as and when required if the patient had any symptoms suggestive of a change in blood sugar. The patients were reminded through automated messaging services and a minimum of 5 days' readings were recorded. They were asked to report the blood sugar charts regularly through telemedicine. The compliance to medication was 88%, which was relatively higher than the 58.5% reported in our study. Yet, 39.16% of the patients reported worsening of hyperglycemia and required additional medications for control of blood glucose. Psychological stress was the most common factor associated with the worsening of hyperglycemia. Both FBG and PPBG during the lockdown were higher than that during the prelockdown period; however, a statistically significant difference was seen only with PPBG.
Contrasting results were seen in a prospective study by Rastogi et al. in North India, which included 422 participants aged between 52 and 64 years, who had access to a home-based glucometer during the lockdown period. They were regularly approached telephonically for consultation and guidance for adjustment of the OAD drugs and/or insulin. They were requested to share glycemic records of FBG and PPBG (1–2 h after a major meal) using the home-available glucometers and get HbA1c tested at the nearest available laboratory facility after a minimum of 3 months of lockdown. There was a reduction in HbA1c by 0.4% (P = 0.005) and PPBG by 42 mg/dL (P < 0.001) from prelockdown to during the postlockdown period. Physical activity increased during the lockdown. The authors reported that recurrent contact through teleconsultations might have helped in reducing the fear and stress of acquiring COVID-19 infection. Other possible factors reported were a decrease in work-related stress, adequate time for self-care, better compliance to medications, adherence to dietary recommendations (home-cooked food), and lack of availability of an outside calorie-dense diet.
In another study in North India, Ghosal et al. interviewed 150 patients telephonically after 45 days of the start of lockdown, regarding lifestyle changes, stress, and other diabetes-related questions. They found that carbohydrate consumption and frequency of snacking increased by 21% and 23%, respectively. Exercise duration was reduced by 42% and weight gain occurred in 19% of the patients. The frequency of SMBG decreased in 23% of the patients. “Mental stress” was reported by 87% of the patients. Availability of medicines and insulin was uninterrupted in 91% of the patients.
Sankar et al. in a study among 110 patients in South India reported that the lockdown did not cause a major change in the overall glycemic control. Ninety percent of the patients had access to medications and overall physical activity and dietary adherence remained unchanged in ≥80% of the patients. There was increased consumption of vegetables and fruits and decreased consumption of unhealthy snacking. No significant change in the mean HbA1c and body weight was noted pre- and postlockdown. The authors hypothesized that increased involvement in household chores could have helped in preventing significant HbA1c and body weight change.
These varying data from different parts of India and results from our study indicate that various factors, which might have influenced diabetic control during the lockdown, are self-awareness among patients, access to home-based glucometers, teleguidance from doctors, urban or nonurban settings and availability of the different types of food. The difference in outcomes between the studies could also be due to the different age groups of the subjects, with the possibility of job-related stress influencing the diet, exercise, and sleep patterns being higher in the younger population. However, teleconsultation rather than automated reminder services seems to have an edge over other modalities, possibly due to the direct human contact factor.
COVID-19 has underscored the need and opportunities for innovations in the delivery of diabetes care through virtual consultations with physicians, and the use of technology. Virtual consultations might also support people with diabetes to be seen by the “right person at the right time” instead of waiting months between routine clinic appointments. It is important to educate diabetic patients regarding the management of their condition during acute illness, including medication changes. It is also critical that there is no deterioration in the medical management of glycemia and other complications of diabetes, which, if neglected, might result in increased morbidity and mortality, independent of COVID-19. During this period, telemedicine can be useful for the management of patients with chronic diseases such as diabetes.,, It has been shown to improve psychosocial outcomes in young diabetic adults. Further, the use of apps can support self-management of chronic conditions, for example, continuous glucose monitoring enables support with diabetes. Adapting new ways of virtual health-care and digital technologies is imperative to allow health-care professionals to continue routine patient care.
There are some limitations to our study. First, it was a single-center retrospective study; hence, the results cannot be generalized. Second, as the records were taken from a database, we could not obtain information about the change in lifestyle, diet, drug availability, and stressors that might have led to an increase in weight and the glycemic parameters. A multi-center study with a large sample size with information about these factors gathered in a face-to-face setting is necessary.
| Conclusion|| |
The results of this retrospective study show that COVID-19 lockdown had a significant effect on glycemic control (HbA1c, FBS, and PPBS) and weight, and patients noncompliant with the treatment may experience a worsening of symptoms. However, this epidemic has taught us how to prepare better in the face of a similar event in future. It is clear that telehealth is the way forward, more so considering that India has the largest number of mobile phone users in the world with wide use even in remote areas.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]