Year :
2023
| Month :
November
| Volume :
17
| Issue :
11
| Page :
LC20 - LC24
Full Version
Prevalence of Diabetes Mellitus and its Associated Risk Factors among Tuberculosis Patients in Sonipat District, Haryana: A Cross-sectional Study
Published: November 1, 2023 | DOI: https://doi.org/10.7860/JCDR/2023/64911.18718
Jagmohan Singh, Anita Punia, Sanjay Kumar Jha, Murugdass Narendran, Sanjeet Singh, Deepika Kataria
1. Postgraduate Student, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat, Haryana, India.
2. Professor, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat, Haryana, India.
3. Professor, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat, Haryana, India.
4. Postgraduate Student, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat, Haryana, India.
5. Associate Professor, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat, Haryana, India.
6. Postgraduate Student, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat, Haryana, India.
Correspondence Address :
Anita Punia,
Professor, Department of Community Medicine, BPSGMC for Women, Khanpur Kalan, Sonipat-131305, Haryana, India.
E-mail: dranitapunia15@gmail.com
Abstract
Introduction: The global increase in Diabetes Mellitus (DM) is a recognised re-emerging risk and challenge to Tuberculosis (TB) control. The bidirectional association between TB and DM is currently one of the major concerns for clinicians. India has the highest prevalence of TB and the second highest prevalence of DM worldwide.
Aim: To estimate the prevalence of DM and its associated risk factors among TB patients in District Sonipat, Haryana, India.
Materials and Methods: A cross-sectional study was conducted to determine the prevalence and factors associated with Diabetes among TB patients registered at the Nikshay portal. A total of 400 patients were interviewed using consecutive sampling technique from eight randomly selected Designated Microscopy Centres (DMCs) in District Sonipat, Haryana , India. To identify associations, a multivariable logistic regression model was applied.
Results: The prevalence of diabetes among TB patients was found to be 16.25% (65/400). The mean age of the study subjects was 39.9±17.3 years. DM was significantly associated with increasing age, literacy, marital status, occupation, smoking, second-hand smoking, duration of smoking, sputum status at the time of initiation of treatment, pulmonary TB, and other chronic diseases such as hypertension and cardiovascular disease.
Conclusion: The present study found a higher prevalence of diabetes among TB patients than in the general population. Therefore, it is recommended to strengthen early bidirectional screening and timely management of TB/DM co-morbidity.
Keywords
Diabetes mellitus, Nikshay portal, Prevalence
Introduction
Non Communicable Diseases (NCDs) like DM are spreading like an epidemic, disproportionately affecting Low- and Middle-Income Countries (LMICs) where the burden of infectious diseases is also high (1). The prevalence of diabetes has increased worldwide due to population ageing, urbanisation, changes in diet, and reduced physical activity patterns resulting in increasing obesity (2). Globally, 537 million adults are now living with diabetes, and the total number of diabetic patients is predicted to rise to 783 million by 2045. In 2021, India alone had 74.2 million people with diabetes, and it is expected to increase to 124.9 million in 2045 (3). The global increase in type II DM is a recognised re-emerging risk and challenge to TB control (4). It has been estimated that nearly 15% of people with TB have diabetes, compared to 9.3% of the general adult population (1),(4). Diabetes is linked to a threefold increase in the risk of TB disease, a twofold increase in the risk of death during TB treatment, a fourfold increase in the risk of TB relapse after treatment completion, and a twofold increase in the risk of Multidrug-resistant TB (MDR-TB) (5),(6),(7).
The DM is caused by a combination of genetic and environmental factors. Both genes and the environment play a significant role in insulin resistance and beta-cell dysfunction (8). The prevalence of DM increases with advancing age, Low Socio-economic Status (SES) (9), a family history of DM (10), unhealthy lifestyle factors (physical inactivity, increased Body Mass Index [BMI], and smoking), and pregnancy (11). Both active and passive smoking increase the risk of developing diabetes, exacerbate the micro- and macrovascular complications of DM, and are also associated with insulin resistance and inflammation (12). People with chronic kidney failure who are on dialysis are 6.9 to 52.5 times more likely to get TB and are also at risk of developing DM (13).
Diabetes is estimated to affect nearly 20% of all TB patients in India, which adversely affects their management (14). The National Tuberculosis Elimination Program (NTEP) has recommended routine testing of diabetes among TB patients in accordance with World Health Organisation (WHO) recommendations (15),(16). There is limited research on DM in TB patients in Sonipat District of Haryana State, India (17). Thus, against this background, the current study was planned with the objective to study the prevalence of diabetes and its associated factors among TB patients currently on treatment.
Material and Methods
This cross-sectional study was conducted among TB patients in District Sonipat, Haryana, India, who were registered under NTEP on the Nikshay portal at Designated Microscopic Centres (DMCs) between August 2021 and August 2022. The study received approval from the Institutional Ethics Committee (BPSGMCW/RC635/IEC/20). The purpose of the study was explained to the participants, and their confidentiality and data privacy were assured throughout the study. After assessing the eligibility of each patient, the purpose of the study was explained, and written consent was obtained.
Inclusion criteria: The study included all TB patients aged 18 and above, including new and retreatment cases, extrapulmonary cases, and MDR cases, who visited the DMC for antitubercular treatment and were willing to participate.
Exclusion criteria: Patients with immunosuppressive disorders like Human Immunodeficiency Virus (HIV) and those already on immunosuppressive treatment were excluded.
DM was diagnosed based on one of the following criteria:
1) Self-reported history of DM and ongoing diabetes treatment.
2) Fasting plasma glucose ≥126 mg/dL (18).
3) Random plasma glucose ≥200 mg/dL (18).
Sample size: The sample size was calculated considering a diabetes prevalence of 20% (19) and an absolute error of 4% at a 95% significance level. Therefore, the final sample size was 400.
Study Procedure
Out of the 16 DMCs in District Sonipat, eleven were operational. A list of all DMCs with the number of registered TB patients was obtained from the District TB Officer and served as a sampling frame. Using a lottery method, eight DMCs were randomly selected. At each selected DMC, 50 eligible TB patients were consecutively sampled to reach the required sample size of 400. As one randomly selected DMC had only 26 registered patients, another DMC was randomly selected to ensure a sample size of 50 for that DMC. Senior TB Laboratory Supervisors (STLS), Senior TB Supervisors (STS), Multi-Purpose Health Workers (MPHWs), Multi-Purpose Worker Supervisors (MPW(S)), and Accredited Social Health Activists (ASHAs) were involved in motivating patients to participate in the study and facilitating blood sugar level testing. Random blood glucose levels were measured on the spot using a glucometer.
A semistructured schedule, which was modified based on a pilot study was conducted on 40 subjects (10% of the sample size) from a neighbouring district. The variables of the semistructured schedule were finalised based on their coefficient of reliability, calculated using Cronbach’s Alpha, with scores of 0.80. The required data were collected using a schedule, which included socio-demographic characteristics such as age, gender, education, occupation, religion, caste, and marital status. Anthropometric measurements for height, weight, and blood pressure were taken.
To measure height, a wall-mounted measuring tape was used without footwear or headgear, and the measurement was recorded in centimetres to the nearest 0.1 cm. Body weight was measured using a portable electronic weighing scale, and the measurement was recorded in kilograms to the nearest 0.1 kg, without shoes, socks, or heavy clothing. Blood pressure was measured three times using a digital automatic blood pressure monitor, following WHO guidelines (20). The measurements were taken from the left arm, with the cuff positioned at the same level as the heart, and the procedure was performed with elbow support using the universal cuff. The average of the three readings for both systolic and diastolic blood pressure was recorded for data analysis.
All eligible TB patients who were diagnosed and registered on the Nikshay portal were screened for DM according to the guidelines specified by the National Programme for Prevention and Control of Non-Communicable Diseases (NPNCD), erstwhile NPCDCS (National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular diseases, and Stroke) (21). Patients with a self-reported history of taking antidiabetic drugs after diagnosis by a medical professional were also considered. TB patients were initially screened using a Random Blood Sugar (RBS) test conducted with a Dr. Morepen glucometer. The waste generated during the procedure was disposed of in accordance with biomedical waste management rules. If the RBS was less than 140 mg/dL, no further tests were conducted, and the patient was labelled as non diabetic. If the RBS was ≥140 mg/dL, a Fasting Blood Glucose (FBS) test was performed. An FBS value ≥126 mg/dL indicated diabetes. Additionally, details about the sputum status at the time of diagnosis (i.e., sputum positive, sputum negative, or extrapulmonary TB) were noted from the TB treatment record.
Statistical Analysis
The collected data were entered into an excel spreadsheet. Analyses were performed using R statistical software version 4.2.1. Descriptive statistics were computed, and the results were presented as mean and standard deviation for continuous variables, and frequency and proportion for categorical variables. To assess associations, either Pearson’s Chi-square test or Fischer’s-exact test was applied. A p-value less than 0.05 was considered statistically significant. Bivariate logistic regression was conducted, and variables with a p-value less than 0.25 were included in the multivariable logistic regression to identify the risk factors for DM among the participants. Finally, variables with a p-value less than 0.05 in the multivariable logistic regression model were considered statistically significant.
Results
A total of 400 TB patients were selected during the study period. The mean age of the study subjects was 39.9±17.3 years. Approximately three-fifths (236) of the TB patients belonged to the economically productive age group of 21-50 years, while 14.5% of TB patients were less than 20 years old. More than half of the study subjects were male, 67.25% resided in nuclear families, 63% resided in rural areas, and 20.5% had completed education up to the matric level (Table/Fig 1).
Prevalence and factors associated with DM among TB patients: The prevalence of DM among TB patients was 16.25% (65/400), with 5.66% (12/212) of patients up to 40 years of age and 28.19% (53/188) in older individuals. The prevalence was 19.85% (26) and 14.49% (39) among those residing in joint and nuclear families, respectively, and 16.27% (41) in rural areas and 16.22% (24) in urban areas (Table/Fig 1). The mean body weight of diabetic TB patients was 56.02±11.67 kg, the mean BMI was 20.48±3.66 kg/m2, and the mean blood pressure was significantly higher in diabetic patients compared to non-diabetic TB patients (Table/Fig 2).
The prevalence of DM was 22.86%, 20.83%, and 13.75% among regular drinkers, social drinkers, and non smokers, respectively.
Among smokers, the prevalence of DM was 23.08%, 22.54%, 19.91%, and 11.64% among current smokers, ex-smokers, passive smokers, and non-smokers, respectively. The prevalence of DM was 21.09% and 5.6% among pulmonary and extrapulmonary TB cases, and 21.42% and 8.59% among sputum positive and negative cases. Those who had thyroid problems, kidney diseases, and liver diseases had a significantly higher prevalence of diabetes (Table/Fig 3).
The multivariable logistic regression analysis of the selected variables, as mentioned in the statistical analysis, revealed that the odds of TB-DM were 38.9 times significantly higher {Adjusted Odds Ratio (AOR)=38.90; Confidence Interval (CI)=1.60-1425.82} in the 51-60 years age group compared to the ≤20 years age group. The odds of DM among pulmonary TB patients were 15.7 times significantly higher (AOR=15.73; CI=1.64-150.49) compared to those with extrapulmonary TB. The odds were 15.0 times higher in hypertension (AOR=15.03; CI=3.76-59.96) and 26.7 times higher in those with kidney disease (AOR=26.72; CI=1.46-487.44), and these associations were statistically significant. The odds of TB-DM were 27.0 times significantly higher for those with a normal BMI (AOR=27.00; CI=4.46-163.29) compared to underweight patients. The influence of factors such as gender, literacy, marital status, alcohol consumption, smoking, second-hand smoking, and sputum status were not significant in the logistic regression (Table/Fig 4).
Discussion
The TB is known to be diabetogenic (22),(23), impairing glucose tolerance (24),(25), and increasing the risk of developing Type 2 Diabetes Mellitus (T2DM) in the future (26). The present study also revealed a higher prevalence of 16.25% (65/400) of DM among TB patients compared to the general population (9.6%) (4), indicating its diabetogenic nature. This risk was shown to increase with age, particularly beyond 40 years, as observed in several other studies [27-33]. The current study also observed a significant increase in prevalence beyond the age group of 50 years. Despite 63% of the study subjects residing in rural areas, the place of residence did not show a difference in prevalence in the current study, possibly due to homogeneity in dietary habits, lifestyles, and exposure to equivalent risk factors in the region.
Literacy plays an important role in comprehension, acceptance of behaviour change communication, treatment compliance, and adoption of favourable lifestyles and habits, all of which are essential for control of TB. Rajaa S et al., also observed the protective effect of literacy in TB-DM prevalence (34). The current study suggests that poor literacy poses challenges to TB control (illiterate crude OR 3.97), while female illiteracy disparity puts the entire family at risk of TB (35). Male TB patients were found to have a higher prevalence of DM in the current study and in other studies conducted elsewhere (30),(31),(34). The higher prevalence of health-damaging lifestyles and habits among males, such as smoking (Table/Fig 4) and alcohol consumption, which were also observed as risk factors for TB-DM in the current study, could contribute to this association.
This was also observed in other studies (30),(36),(37). Males also become vulnerable to increased exposure due to travel, social and working environments, thus increasing their risk.
Literature has observed a higher prevalence of DM among cases of pulmonary TB compared to extrapulmonary cases (30),(32),(38). The current study also observed a significantly higher prevalence of DM among pulmonary cases (pulmonary adjusted OR 15.73, (Table/Fig 4)). DM also compromises their immunity further (3),(39), reflecting in a higher prevalence of positive sputum status (27),(29),(34),(36),(37) among them (Table/Fig 4), persisting as potential sources of TB transmission.
Co-morbidities such as higher BMI, hypertension, and renal diseases, which are known to cause diabetes, were found to be significantly associated with TB-DM co-morbidity in the current study (Table/Fig 4). With the exception of the lack of association between BMI and TB-DM in Ethiopia (38), these chronic co-morbidities were found to significantly contribute to the condition in various studies (30),(31),(33), highlighting the need for their monitoring and management to ensure the possibility of remission for TB-DM. Similar findings have been mentioned in other studies [27,29-34,36-38] (see (Table/Fig 5)).
Limitation(s)
The present study has a few limitations. The data collection used consecutive sampling, so it may not be truly representative of TB-DM patients. The present was a cross-sectional study, and the study subjects were not followed-up after a single visit, so there is a possibility that some study subjects could have developed DM during the course of Antituberculosis Treatment (ATT). Details of tobacco use and DM treatment practices/daily drug adherence were self-reported and not verified. The generalisability of the present study is limited to the district only.
Conclusion
The prevalence of DM among TB patients was 16.25%. TB patients with profiles of >40 years, being married, illiterate, smoking, exposed to second-hand smoking, with pulmonary TB, sputum positive, wit BMI in the overweight and above range, and with co-morbidities of hypertension and cardiovascular disease were observed to be significantly more prone to diabetes. It is recommended that bidirectional screening for TB and diabetes be strengthened among patients with such profiles to ensure favourable outcomes in their TB treatment.
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DOI: 10.7860/JCDR/2023/64911.18718
Date of Submission: Apr 21, 2023
Date of Peer Review: Aug 02, 2023
Date of Acceptance: Sep 23, 2023
Date of Publishing: Nov 01, 2023
AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? Yes
• For any images presented appropriate consent has been obtained from the subjects. NA
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ETYMOLOGY: Author Origin
EMENDATIONS: 6
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