Weight Changes and its Determinants among Sputum Positive Pulmonary TB Patients in Bengaluru – A Prospective Study

Introduction

Tuberculosis (TB) is a major cause of ill health being a communicable disease and is one of the leading causes of death worldwide. Until the Coronavirus (COVID-19) pandemic, TB was the leading cause of death from a single infectious agent, ranking above HIV/AIDS. TB is caused by the bacillus Mycobacterium tuberculosis, mainly affecting the lungs though other parts of the body can also be involved.¹ About 10% of latent infections progress to active disease. Latent infection kills about half of those affected if left untreated. About one-fourth of the world’s population is infected with TB.² Tuberculosis is a global pandemic resulting in an estimated 5.8 million new cases globally in 2020. This drop of cases from 7.1 million in 2019 was due to the COVID-19 pandemic.1 An estimated 1.63 million new cases were registered in India in 2020, which is 0.5 million cases lower than 2019. India contributed to 41% of the global drop in cases in 2020, the highest among all nations.³

Undernutrition increases the risk of tuberculosis (TB) and in turn TB can lead to malnutrition. Undernutrition is therefore highly prevalent among people with TB. It has been demonstrated that undernutrition is a risk factor for progression from TB infection to active TB disease and that undernutrition at the time of diagnosis of active TB is a predictor of increased risk of death and TB relapse.⁴ Underweight indicating undernutrition has a bidirectional relationship with TB and is an established prognostic risk factor. It contributes to an estimated 55% of annual TB incidence in India. Positive weight changes among Indian patients without additional nutritional support are in the range of 3–4 kg. Undernourished patients with TB get into a vicious cycle of worsening disease and undernutrition, which is detrimental.⁵

The treatment outcomes of TB patients can be improved by improving their nutritional status. Incorporating nutritional support and monitoring the nutritional status during the course of treatment increases the probability of favorable treatment outcomes.⁶ Many factors like the associated co-morbidities, personal habits, adverse drug reactions (ADRs) of the drugs, socio economic status, etc. might affect the weight gained during the course of the treatment. Weight changes during the course of treatment is one of the important indicator of nutritional status of the patients.⁵ Assessment of the same along with various factors which may affect the weight changes will help in improving the nutritional status of the patients, which in turn gives successful treatment outcomes.

Objectives

• To study the weight changes and its determinants among newly diagnosed drug sensitive smear positive pulmonary TB patients on Fixed Dose Combinations (FDCs).

• To estimate the prevalence of undernutrition among the study subjects.

Materials & Methods

An observational prospective study was conducted in Tuberculosis units (TUs) and Peripheral health institutes (PHI) of BBMP area. For logistics purpose, among three zones in BBMP, west zone was selected; out of which five TUs namely Nandini layout, Geleyarabalaga, Yeshwantpur, Palace Guttahalli and Sultanpalya was selected randomly. Newly diagnosed smear positive drug sensitive pulmonary TB cases, ≥ 18 years of age, who were on daily regimen taking the anti-tuberculosis treatment (ATT) FDCs as prescribed according to the weight of the patient were included. HIV positive patients, critically ill, moribund, bedridden or unconscious patients, MDR- TB cases, patients with pre-existing liver and kidney diseases were excluded. The patients were recruited from August 2019 to June 2020. Last patient was recruited in the last week of June 2020 and was followed up till the end of August 2020. A pre-tested semi-structured questionnaire was used. In a study carried out by Shukla A et al.,⁷ the prevalence of undernutrition was 79.5%. In this present study, expecting a similar proportion, considering relative precision of 10% and confidence level of 95%, the sample size was calculated to be minimum of sputum positive Pulmonary tuberculosis (PTB) cases. The final sample size was calculated as 121.

Sampling technique

Step 1: Selection of TU: Probability sampling – Simple random sampling

BBMP has three zones in which 24 TUs are present. Out of the three East, South and West zones, due to logistic purposes, west zone was selected. Totally, five TUs namely Nandini layout, Geleyarabalaga, Yeshwantpur, Palace gutthalli and Sultanpalya were selected randomly. Cases registered in the selected TUs and their peripheral health institutions (PHIs) were included in the study. Patients were recruited from August 2019 to December 2020 and were followed up to June 2020. Follow up of patients in person was difficult during March 2020 to June 2020 because of the COVID-19 pandemic.

Step 2: Selection of cases: Non - probability sampling

Smear positive drug sensitive new PTB patients consenting to the study were recruited from the selected TU in the defined quarters of the study period.

Method of data collection

Ethical clearance was obtained from the Institutional ethical committee of M.S. Ramaiah Medical College, Bangalore. Prior permission was taken from the concerned authority, District TB officer of BBMP, Bengaluru to conduct the study in the selected TUs. Recruitment of the study subjects and baseline measurements: All newly diagnosed smear positive drug sensitive pulmonary TB patients registered in the selected tuberculosis unit in the BBMP area during the study period (August 2019 to June 2020) were recruited. After obtaining the written informed consent, a pretested semi-structured questionnaire was administered to collect the baseline data on socio demographic data, housing environment and clinical characteristics. Laboratory and other relevant data were captured from the patient records maintained at the TU or PHI. Further, if the patients agreed for visit to their house, visit was made along with Tuberculosis Health Visitors (TBHV) to document the housing conditions such as presence of smoke outlet in kitchen, ventilation, lighting, overcrowding etc. In the eventuality of the patients who did not permit us to visit their house, details were obtained through oral interview. Anthropometric measurements like height and weight were recorded to assess weight changes. Follow-up: Weight changes during the course of treatment were measured at the start of the treatment, at the end of two months and at the end of six months respectively.

Operational definition of underweight

The values for body mass index (BMI) are ageindependent for adult populations and are same for both the genders. The cut-off point of BMI less than 18.5 kg/ m² was considered for underweight.⁸ Data collected was entered into an MS Excel sheet and was then exported into IBM SPSS statistics version 18. All the quantitative parameters such as age, height, weight etc. were expressed as mean and standard deviation or median and interquartile range and also by using frequency and percentage. The strength of association was expressed as univariate odds ratio with a 95% confidence interval. All the factors which had a p value of <0.05 in univariate analysis were included for the forward multiple logistic regression analysis and was expressed as multivariate odds ratio with a 95% confidence interval. Repeated ANOVA measures were used to see statistical differences in the weight changes between groups.

Results

In the present prospective study, 121 study subjects were recruited and were followed up for whole of treatment course i.e six months. Among 121 subjects, 70 (57.9%) were males. Median age of the study subjects was 37 (IQR: 49.5-26.5) years with mean weight and height of 55.72 ± 8.9 kg, 159.5 ± 7.2 cm respectively. Majority of study population, 42 (34.7%) were in the age group of 18-29 years, out of which 16 (39.1%) were males and 26 (60.9%) were females. More than fifty percent of males were in the age group of 30 to 49 years and among females, majority 26 (51%) were present in the age group of 18-29 years.

Majority of the study subjects belonged to Hindu religion, married, belonging to a nuclear family and resided in slum areas. More than fifty percent of study population had literacy levels of less than high school and majority were either homemakers or students in employment status. Almost fifty percent of the study population belonged to lower middle class according to modified Kuppuswamy scale. Majority had separate kitchen with smoke outlets. In more than fifty percent households, overcrowding and inadequate ventilation was noted. Any form of tobacco use was present in 40 (33.1%) of study subjects with similar proportion consuming alcohol (Table 1, 2).

The difference in weight changes between the measurements at the baseline, two and six months respectively was found to be statistically significant with p value <0.001. Mean weight gain in the study subjects was 2.3±1.4 kg. An average of 4% positive weight change was seen at the end of the treatment (Table 3).

The direct benefit transfer of rupees five hundred was low at the recruitment due to either unavailability of bank account under the subject’s name or Aadhar card. The proportion of the study subjects availing this benefit increased at the end of two and six months follow-up period. The utilization of NPY money for other purposes like pooling into family income or using it for transportation or other medicines was more (41, 38.3%) rather than its utilization for nutritional support (Table 4).

Diabetes mellitus, hypertension and cardiovascular diseases were the most commonly reported comorbidities by the study subjects. Almost half of the study population had pallor. Though majority of the subjects had a normal BMI, fifteen percent had BMI less than 18.5 kg/m2 classified as undernutrition (Table 5). They were counselled for proper dietary intake and nutritional supplements.

Positive weight changes were significantly associated with higher socio economic status, absence of alcohol consumption, absence of tobacco use, absence of clubbing and pallor in TB patients; while only absence of pallor [OR-16.1(69.3-3.7)] and tobacco use [OR12.6(43.9-3.5)] in multivariate analysis were with p value < 0.05 (Table 6).

Discussion

In this study, positive weight changes were observed in all the patients with average weight gain of 1.1 to 3.7 kg with an average of 4% positive weight change observed at the end of the treatment. There was an increase in the mean weight gain throughout the course of the treatment. This outcome is similar to the 3-4 kg of weight gain among Indian patients according to the nutritional guidance document.⁵ A similar study in the US showed an average weight gain of 2 to 5 kg and 5% increase at the end of treatment course.⁹ Another study in Malaysia showed positive weight changes similar to our study at the recruitment, at the end of two months and six months.¹⁰ The differences might be due to the difference in sampling size, population and study setting. Although these findings are encouraging in terms of the efficacy of treatment and favourable treatment outcomes, earlier researchers have alerted that weight gain during treatment may be mostly due to accumulated fat mass, and patients may fail to restore body protein by the end of treatment.¹⁰ Current study shows the factors like higher socio economic status, absence of alcohol consumption, absence of tobacco use, absence of clubbing and pallor in TB patients are significantly associated with positive weight gain. Similarly, higher odds of lower BMI was found to be associated with the use of tobacco and alcohol consumption in a study conducted by Shukla et al. 7 Positive weight changes is one of the prognostic factor for successful treatment. Weight change in this study was 1.1 to 3.6 kg, which is suboptimal. Additional nutrition support and counseling is critical for optimal weight change during the treatment course. Nutritional support is always considered a good adjuvant therapy for TB patients. The government of India provides financial support to all TB patients for their nutritional needs under the Nikshay Poshan Yojana (NPY) through direct benefit transfer (DBT) into the bank account of the beneficiary since 2018. National TB Elimination Program (NTEP) is one of the first health programs in India to use DBT. At the end of this study, more than 90% of patients received nutritional support through DBT. The main reason for not receiving the NPY support was due to the absence of Aadhar card. The utilization of NPY money for other purposes like pooling into family income or using it for transportation or other medicines was more rather than its utilization for nutritional support. This was mainly due to lack of awareness about the importance of supplementary nutrition.

Positive weight change is one of the prognostic factor for successful treatment. Weight change in this study was 1.1 to 3.6 kg, which is suboptimal. Additional nutrition support and counseling is critical for optimal weight change during the treatment course. In this study, the prevalence of undernutrition was fifteen percent, which is very low when compared to Indian undernutrition prevalence of fifty five percent in new TB cases. Another study in India by Shukla et al., showed very high prevalence of 79.5%⁷ in Nepal, 33%¹¹ in Ethiopia. The pooled prevalence was 50.8% in a systematic review and meta-analysis study¹² and in another crosssectional study, it was 40%.¹³ This variation may be due to the differences in study populations, dietary patterns, associated co-morbidities, body compositions, ability to purchase, lack of awareness, etc.

Conclusion

Further research on biochemical and functional nutritional assessment is necessary to assess the actual nutritional status of TB patients. The in-depth study of various factors associated with undernutrition in TB patients, the role of supplementary nutrition and nutritional counselling is necessary as the nutritional status of TB patients is an important determinant of the favourable treatment outcome. The strength of the study was follow-up at the end of two and six months respectively for weight gain which gave complete picture of weight changes during the course of treatment. In the present study, though all the TUs were selected from West zone, the results can be generalized as most of the TU’s structure and profile is similar. The limitations were that dietary assessment, biochemical and functional nutritional assessments which are better indicators of nutritional status were not assessed in the current study.