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ORIGINAL ARTICLE
Year : 2022  |  Volume : 66  |  Issue : 5  |  Page : 71-75  

Seroconversion and side effects after COVID vaccination among persons with type 2 diabetes in urban, rural, and tribal areas in Kerala, India


1 Senior Resident, Department of Community Medicine, Amrita Institute of Medical Sciences, Kochi, Kerala, India
2 Professor, Department of Community Medicine, Amrita Institute of Medical Sciences, Kochi, Kerala, India
3 Assistant Professor, Department of Community Medicine, Amrita Institute of Medical Sciences, Kochi, Kerala, India
4 Professor, Pain and Palliative Care Department, AIMS, Kochi and Head, Amrita Kripa Charitable Hospital, Wayanad, Kalpetta, Kerala, India

Date of Submission11-Aug-2022
Date of Decision20-Aug-2022
Date of Acceptance23-Aug-2022
Date of Web Publication11-Nov-2022

Correspondence Address:
Aswathy Sreedevi
Department of Community Medicine, Amrita Institute of Medical Sciences, Kochi, Kerala
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.ijph_1096_22

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   Abstract 


Background: Persons with type 2 diabetes mellitus (T2DM) are at high-risk for COVID-19 infection and are a priority group for vaccination. Objectives: The objective of this study is to estimate the seroconversion and determine the side effects after COVID-19 vaccination among persons with T2DM in urban, rural, and tribal areas in Kerala. Methods: A cross-sectional study was conducted in urban, rural, and tribal field practice areas of a medical college in Central Kerala, among 396 persons with T2DM. The participants were selected by simple random sampling from the 200–250 diabetic patients visiting each health center. Qualitative and quantitative estimation of antibodies were done by WANTAI Ab enzyme-linked immunosorbent assay kit and Abbott SARS COV-2 IgG Quantitative assay, respectively. Results: The mean age of the respondents was 59.40 ± 12.25 years. A majority (65.5%) had received both doses of vaccine. About half (51.5%) experienced side effects after vaccination. Antibodies (IgG or IgM) were detected in 93.2% (95% confidence interval [CI] 90.2, 95.5) of participants. Those with a duration of diabetes ≥5 years, with a single dose of vaccine, were five times (adjusted odds ratio [aOR] – 5.23,95% CI 1.86, 14.66) and four times (aOR – 4.11, 95% CI 1.66, 10.13) more likely, respectively, to be seronegative. Those who took medication for diabetes were protected against a no antibody (aOR – 0.05, 95% CI 0.02, 0.148) response. The median antibody titer in a subset (150) of participants was 365.2 (90–1587) AU/ml. Past COVID infection was an independent determinant of high IgG titers (aOR – 4.95, 95% CI 1.50, 16.36). Conclusion: Reinforcing the importance of vaccination particularly among those with longer duration of diabetes is imperative.

Keywords: COVID-19, seroconversion, type 2 diabetes mellitus, COVID vaccine, antibody titer


How to cite this article:
Sasidharan N, Sreedevi A, Mohandas S, Tomy C, Vasudevan S, Diabetes Seroconversion Study Team. Seroconversion and side effects after COVID vaccination among persons with type 2 diabetes in urban, rural, and tribal areas in Kerala, India. Indian J Public Health 2022;66, Suppl S1:71-5

How to cite this URL:
Sasidharan N, Sreedevi A, Mohandas S, Tomy C, Vasudevan S, Diabetes Seroconversion Study Team. Seroconversion and side effects after COVID vaccination among persons with type 2 diabetes in urban, rural, and tribal areas in Kerala, India. Indian J Public Health [serial online] 2022 [cited 2022 Dec 4];66, Suppl S1:71-5. Available from: https://www.ijph.in/text.asp?2022/66/5/71/360653

Diabetes Seroconversion Study Team
Dr Ameena Thaha, MBBS, MD Resident, Microbiology
Dr Sumithra S, Lecturer in Biostatistics, St John's Medical College, Bangalore
Dr Prem Nair, MD, Medical Director, Amrita Institute of Medical Sciences, Kochi





   Introduction Top


COVID-19 is an infectious disease caused by a newly discovered coronavirus. COVID-19 has affected over 100 million people and inflicted over 2 million deaths globally.[1] The disease has a poor prognosis among the immunocompromised. The available evidence also suggests a reduced vaccine response in people who are immunocompromised. This is a phenomenon seen across COVID-19 vaccines largely mRNA, for which evidence is available.[2]

Vaccine effectiveness of two doses of mRNA COVID-19 vaccine against COVID-19-associated hospitalization was lower among immunocompromised patients at 77% compared to immunocompetent patients at 90%.[3] Among different categories of immunocompromised, a systematic review showed a decreasing seropositivity; 92% for patients with solid cancer, 78% for patients with immune-mediated inflammatory disorders, 64% for patients with hematological cancer, and 27% for recipients of transplants.[4] COVID-19 breakthrough infection has also been higher among those who received a single dose of immunization, those with immune dysfunction, such as HIV infection, rheumatoid arthritis, and solid organ transplant compared with persons without immune dysfunction.[5] However, studies on more common immunocompromised condition such as diabetes are lacking.

Among persons with type 2 diabetes mellitus (T2DM), the outcomes are severe disease, intensive care unit admissions, and increased mortality.[6] Interacting with other risk factors, hyperglycemia might modulate immune and inflammatory responses, thus predisposing patients to severe COVID-19 and possible lethal outcomes.[7] Hyperglycemia in diabetes is thought to cause dysfunction of the immune response, which fails to control the spread of invading pathogens in diabetic subjects.[8] The common features associated with both diseases are dysregulated immune and inflammatory responses.[9] Therefore, primary prevention (vaccination) remains the mainstay for mitigating risks. Every one in five adults is affected by type 2 diabetes in Kerala,[10] and therefore, it is imperative to understand the seroconversion rates among persons with diabetes. Pneumococcal and Influenza vaccines elicit mild adverse effects among persons with T2DM.[11] Therefore, the objective of this study was to estimate the seroconversion after COVID-19 vaccination among persons with diabetes in urban, rural, and tribal field practice areas of a tertiary care institute in Kochi, Kerala and to determine the side effects after COVID-19 vaccination.


   Materials and Methods Top


A cross-sessional study was conducted among urban, rural, and tribal field practice areas of AIMS, Kochi, from November to January 2022. The Institutional ethical clearance (ECASM-AIMS-2021-388) was obtained. Known diabetic patients >the age of 40 years who had received at least a single dose of any COVID-19 vaccination 14 days before were included in the study after obtaining informed consent. Those who were currently COVID-19 positive or those who had contracted COVID-19 within 3 months were excluded from the study.

Sample size

Based on the seropositivity of 84.6%[12] among persons with diabetes, the minimum sample size was calculated with 10% relative precision and 95% confidence interval (CI), to be 74.

Sampling technique

The study participants were selected by simple random sampling technique from the list of 200–250 diabetic patients visiting each of the rural (Njarakkal), urban (Kaloor), and tribal centers (Kalpetta) of AIMS, Kochi. A total of 396 participants were included in a proportion varying from 40% (159) in rural, 34.5% (137) in urban, and 25% (100) in tribal.

Study instrument

A pretested, semi-structured questionnaire was used to collect data from the study participants regarding sociodemographic, history of comorbidities, and vaccination details. Anthropometric measurements such as height, weight, body mass index, and blood pressure were measured. Serum samples were screened using WANTAI SARS-CoV-2 total IgG and IgM enzyme-linked immunosorbent assays (Beijing Wantai Biological Pharmacy Enterprise Co., Ltd., China) which detects antibodies against the receptor-binding domain of SARS-CoV-2 spike protein. The ratio of absorbance (A) to cutoff (C.O.) (A/C.O. <1) was interpreted as having no SARS-CoV-2 antibodies (negative) and ≥1 having SARS-CoV-2 antibodies (positive). Quantitative IgG antibodies were determined using the SARS-CoV-2 IgG II Quant assay (Abbott Diagnostics, Chicago, IL, USA) which detects antibodies to the receptor-binding domain of the S1 subunit of the spike protein of SARS-CoV-2. The analytical measurement interval is stated as 21–40,000 AU/ml, and positivity cutoff is ≥50 AU/ml. The quantitative assay was carried out in a subset of 150 positive population (50 each from urban, rural, and tribal area). The obtained values were log-transformed.

Statistical analysis

Data collected were entered into an Excel sheet and analyzed using SPSS 21 IBM SPSS Statistics for Windows, version 21(IBM Corp., Armonk, N.Y., USA). Qualitative variables were expressed as frequencies or percentages. Quantitative variables were expressed as mean and standard deviations for parametric data and as the median and interquartile range (IQR) for nonparametric data. Seroconversion was expressed as a percentage with 95% confidence limit. The Chi-square test was done to find the association between variables. Factors associated with the absence of seroconversion were carried out using logistic regression. Along with age and gender, variables that were significant in the bivariate analysis were subjected to multivariable logistic regression analysis. Antibody titer was categorized into tertiles and multinomial regression was carried out to assess the determinants associated with highest tertile of antibody titer. The significance level was set at 5%.


   Results Top


More than half of 210 (53.5%) of the study participants were >the age of 60 years and more than half 216 (54.5%) were women. Regarding morbidity status, 170 (42.7%) were obese according to the Asia-Pacific classification for obesity and less than a third 122 (30.8%) had hypertension. The majority of the study participants, 336 (84.8%) had taken Covishield and 60 (15.2%) had taken Covaxin. About 257 (64.9%) had received both doses of vaccination [Table 1].
Table 1: Profile of the study participants (n=396)

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The majority, 296 (74.7%) of the persons with diabetes were on oral hypoglycemic agents. Of the 359 (90.7%) on medication for diabetes, only 339 (85.6%) were taking medications regularly. About one-fifth of 76 (19.2%) had experienced a delay in getting vaccination. This was mainly due to the nonavailability of vaccine slots and also as few (29.3%) had contracted COVID-19. About 53.5% (212) had experienced side effects after any dose of COVID-19 vaccination. Among the side effects fever was the most common presentation 203 (51.3%) followed by injection site pain 111 (28%), myalgia 70 (17.7%), and others 33 (8.3%).

Seroconversion after COVID-19 vaccination among the study population was estimated to be 93.2% (95% CI 90.2, 95.5). The tribal population had the highest seroconversion (94%, CI 87.4, 97.8), and it was marginally lesser among the urban (93.2%, CI 87.9, 97.0) and rural (92.5%, CI 88.4, 96.59) population.

In the univariate analysis, seropositivity was higher among the younger study participants in the 40–59 and 60–79 age groups when compared to ≥80 years although this was not significant. Although seropositivity was greater among women when compared to men and also greater among tribal population it was not statistically significant. Seropositivity was higher at 199 (95.7%) among the patients with duration of diabetes <5 years when compared to 177 (90.4%) in those with duration of diabetes ≥5 years (P = 0.03). Persons who are taking medications for diabetes had higher seropositivity (95.5%) when compared to those who are not on medication (P < 0.001). Seropositivity was significantly associated with Covishield 320 (95.2%) than with Covaxin 49 (81.7%) and also in those who had taken both doses of vaccine 246 (95.7%) when compared with those who had taken only one dose 123 (88.5%). Although the proportion of persons with a history of COVID infection was significantly associated with antibody positivity, this variable was not considered in multivariate analysis due to sparse data.

On multivariable logistic regression, the independent determinants of an absence of seroconversion were those who have diabetes duration of ≥5 years and those who took a single-dose vaccine. Those who had a duration of diabetes more than or equal to 5 years were five times (adjusted odds ratio [aOR] – 5.230, 95% CI 1.866, 14.660) more likely to not have seroconverted. Similarly, those who had a single dose of vaccine were four times (aOR – 4.111, 95% CI 1.668, 10.131) more likely to not have seroconverted. Those who took medication for diabetes were found to be protected against an absence of antibody response [Table 2]. In addition, subgroup analysis done among the COVID-negative group revealed that the duration of diabetes was associated with the presence of antibodies adjusted for age and sex (P = 0.05).
Table 2: Independent determinants of absence of seroconversion among study participants (n=396)

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Quantitative assessment of COVID IgG antibody titer was done among a subset (150) of the sample. The median antibody titer was 365.2 (90–1587) AU/ml. The median value among those with a single dose of vaccination was 260.2 (IQR 2552) and it nearly doubled for those who had taken both doses to 449.85 (IQR 1437.68). The median log transformed IgG values are similar, varying from 2.56 (1.01), 2.67 (1.39), and 2.24 (1.12) for the urban, rural, and tribal areas, respectively [Figure 1].
Figure 1: Box plot representing the distribution of Log IgG titer according to the place of residence (n = 150)

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IgG titer values of subset of the population were divided into tertiles. Multinomial logistic regression showed that persons with a history of previous COVID infection were more likely to be associated with the highest tertile of antibody titer levels (>942.60) adjusting for age and gender (aOR – 4. 957, CI 1.50, 16.36) compared to lowest tertile.


   Discussion Top


Seroconversion among the persons with T2DM from the tribal, rural, and urban areas was found to be 93.2% (95% CI 90.2, 95.5). Duration of diabetes of >5 years, and those who had received a single dose of vaccine were found to be at higher risk for nonseroconversion whereas being on medication facilitated seroconversion. Seroprevalence was marginally higher among tribal population (94%) followed by the urban (93.2%) and rural population (92.5%). High Antibody titers (>942.60AU/ml) were found to be significantly determined by a history of previous COVID infection.

In a Pan-India study among health-care workers, although the overall seropositivity was 95%, persons with diabetes had significantly lower seropositivity of 84.6% which was lower than in this study 93.2%. The trends of lower seroconversion in those with longer duration of diabetes were observed in the health-care worker study also. In the present study, the less than 5 years of T2DM had 95% seroconversion compared to 90% among those with >5 years.[12]

In Kuwait, antibody titer after COVID-19 vaccination among 81 diabetics and 181 nondiabetic persons, showed that SARS-CoV2 IgG titers were lower in people with T2DM (mean IgG value 138 ± 59.4 BAU/ml), whereas in this study median level of IgG antibody was 365.2 AU/L.[13]

Those with a single dose of vaccination were found to be four times at higher risk of not seroconverting. The seroconversion was 95.7% among those who had taken two doses compared to 88.5% among those who had taken only one dose. This has also been seen in other studies among the immunocompromised such as 92% among those with solid cancer, 78% for patients with immune-mediated inflammatory disorders, 64% for patients with hematological cancer, and 27% for recipients of transplants.[4] Breakthrough infections have also been found to be higher among those who received a single dose of immunization, those with immune dysfunction, such as HIV infection.[5]

Antibody titers were found to be five times higher among those with a history of previous COVID infection. Similarly, in a group of patients with autoimmune rheumatic diseases who had previously had COVID-19, a single dose of vaccine provided a higher humoral response than did two doses of vaccine in infection-naive patients.[14]

In a review by Pal et al.[11] the common side effects following COVID vaccination among persons with diabetes worldwide in the short-term were mild-to-moderate pain at the injection site, fatigue, and headache for Pfizer vaccine, flu-like illness, injection site reactions, headache, and asthenia for Sputnik and injection site pain, headache, fatigue, fever, and nausea or vomiting, etc., for Covaxin. In another study done by Pokharel et al.,[15] in 2021 among 220 health-care workers, common side effects were pain at the injection site (80.90%), fatigue (40.09%), headache (19.54%), chills (8.18%), fever (2.27%), etc., after administration of Covishield vaccine. In the present study, fever (51.3%) was the most common side effect followed by injection site pain (28%), myalgia (17.7%), and headache (5.5%).

Although the seroconversion trends are aligned with trends from other studies, they may not be generalizable to all as the participants are from the list attending the health centers and their health-seeking behavior may be better. Moreover, seroconversion cannot be exclusively attributed to vaccination as it may also be due to natural infection with COVID. The factor of taking medication is associated with higher seroconversion which may be a proxy for glycemic control. However, as HbA1c/previous FBS value has not been collected it is difficult to know the role of glycemic level.


   Conclusion Top


Reinforcing the importance of two doses of vaccine, particularly among those with a longer duration of diabetes is imperative. Hybrid infection can produce high antibody levels.

Acknowledgment

The authors acknowledge the inputs from Dr. Ahmad Mohammad, Dr. Anisur Rahman, WHO Country Office, India, Ms. Minu Maria Mathew, Dr. Saanu S, Dr. Seenu Shaik Sulaiman, Ms. Anima Raj, Mrs. Prajitha, Mr. Ratheesh Kumar R, Mrs. Kavitha P, Mrs. Prameela T K in the conduct of the study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

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Parker EP, Desai S, Marti M, Nohynek H, Kaslow DC, Kochhar S, et al. Response to additional COVID-19 vaccine doses in people who are immunocompromised: A rapid review. Lancet Glob Health 2022;10:e326-8.  Back to cited text no. 2
    
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Adzerikho RD, Aksentsev SL, Okun' IM, Konev SV. Letter: Change in trypsin sensitivity during structural rearrangements in biological membranes. Biofizika 1975;20:942-4.  Back to cited text no. 4
    
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Roberts J, Pritchard AL, Treweeke AT, Rossi AG, Brace N, Cahill P, et al. Why is COVID-19 more severe in patients with diabetes? The role of angiotensin-converting enzyme 2, endothelial dysfunction and the immunoinflammatory system. Front Cardiovasc Med 2020;7:629933.  Back to cited text no. 9
    
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India State-Level Disease Burden Initiative Diabetes Collaborators. The increasing burden of diabetes and variations among the states of India: The global burden of disease study 1990-2016. Lancet Glob Health 2018;6:e1352-62.  Back to cited text no. 10
    
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Shenoy P, Ahmed S, Paul A, Cherian S, Umesh R, Shenoy V, et al. Hybrid immunity versus vaccine-induced immunity against SARS-CoV-2 in patients with autoimmune rheumatic diseases. Lancet Rheumatol 2022;4:e80-2.  Back to cited text no. 14
    
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