ASSOCIATION OF TREATMENT OUTCOME IN RNTCP
PATIENTS IN TRIVANDRUM DISTRICT WITH DIABETES
STATUS- A CASE CONTROL STUDY
DR SHABNA D S
Dissertation submitted in partial fulfillment of the
requirement for the award of the degree of
Master of Public Health
ACHUTHA MENON CENTRE FOR HEALTH SCIENCE STUDIES
SREE CHITRA TIRUNAL INSTITUTE FOR MEDICAL SCIENCES
AND TECHNOLOGY, TRIVANDRUM
Thiruvananthapuram, Kerala. India-695011
October, 2015
Acknowledgements
Foremost, I would like to express my sincere gratitude to my guide Dr. Dr. V. Raman Kutty,
Professor Achutha Menon Centre for Health Science Studies (AMCHSS) for his supervision,
advice and guidance throughout the time of research and writing this thesis. I could not have
imagined having a better supervisor and mentor for my study. This work would not have
been possible without the support and encouragement from the Department of Health and
Family Welfare, Government of Kerala. I offer my special thanks to the department for
permitting me to conduct this research and for all the supports I received during my field
visits.
I would like to thank all the faculties at AMCHSS: Dr.KR Thankappan, Dr. PS Sarma,
Dr. TK Sundari Ravindran, Dr. Mala Ramanathan, Dr. K Srinivasan, Dr. Biju Soman,
Dr. Ravi Prasad Varma, Dr. Manju R Nair, and Ms. Jissa VT for providing their valuable
suggestions to improve the study.
Collective and individual acknowledgements are also owed to project staffs, especially
Dr GK Mini, Neena Elizabath Philip, PhD and my wonderful colleagues especially Pritty
Titus, Atulya Thomas, Dr TijoGeorge, Nayana, Dr Sambit Kumar Behera, Dr Aakshi Kalra
for their constant help and encouragement.
I am grateful to the study subjects and their families who participated or declined to
participate in the study, without whom, I would not have been able to conduct this piece of
work.
I cannot end without thanking my family on whose constant encouragement, support, care,
and love I have relied throughout my time in AMCHSS.
CERTIFICATE
I hereby certify that the work embodied in this dissertation titled “Association of treatment
outcome in RNTCP patients in Trivandrum district with diabetes status- A case control
study” is a bonafide record of original research work undertaken by Dr. Shabna DS, in partial
fulfillment of the requirements for the award of the degree of Master of Public Health, under
my guidance and supervision.
Guide:
DR. V. RAMAN KUTTY
Professor
Achutha Menon Centre for Health Science Studies
Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum
Thiruvananthapuram, Kerala. India-695011
October, 2015
DECLARATION
I hereby declare that this dissertation work titled ‘Association of treatment outcome in
RNTCP patients in Trivandrum district with diabetes status- A case control study, is an
original work of mine and it has not been submitted to any institution or university for the
award of any degree or diploma. Information derived from the published or unpublished
work of others has been duly acknowledged in the text.
DR SHABNA DS
Achutha Menon Centre for Health Science Studies
Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum
Thiruvananthapuram, Kerala. India-695011
October, 2015
Dedicated
to
“RnTCP Family”
TABLE OF CONTENTS
Abstract
1 Introduction and review of literature
1.1 Background. 1
1.2 Tuberculosis(Global, Indian, Kerala scenario) 2
1.3 RNTCP (Revised National Tuberculosis Control Programme) 4
1.4 Global Goals, targets and indicators for TB control 5
1.5 NPCDCS ((National Programme for control and prevention of Cancer,
Diabetes
Cardiovascular disease, and Stroke)
1.6 Socio economic and demographic factors influencing tuberculosis 6
1.7 BMI (Body Mass Index) and Tuberculosis 8
1.8 Alcohol consumption and factors associated 8
1.9 Tobacco usage and associated factors 10
1.10 Diabetes and associated factors 11
1.11 Glycemic control and factors associated 14
1.12 Tuberculosis treatment related factors 15
1.13 Rationale of the study 16
1.14 Research questions 16
1.15 Objectives 16
2 Methodology
2.1 Study type 17
2.2 Study setting 17
2.3 Study population 17
2.4 Time frame 17
2.5 Sample size 17
2.6 Criteria 18
2.7 Sample selection procedure 18
2.8 Method of data collection 19
2.9 Data cleaning 19
2.10 Data storage 19
2.11 Data analysis and statistical method 20
2.12 Study variables 20
2.13 Ethical consideration 22
3 Chapter : Results
3.1 Sample characteristics 23
3.2 Results of bivariate analysis 31
3.3 Results of multiple logistic regression analysis 32
4 Discussion 33
5 Conclusion 41
5.1 Strength of the study 41
5.2 Limitation of the study 42
References
Abbreviations
Annexures
1 Structured interview schedule-English
2 Structured interview schedule- Malayalam
3 Research subject information sheet and consent
form
LIST OF TABLES
3.1 Socio-demographic details 24
3.1b Socio-demographic details(2) 25
3.2 Tobacco use and related factors 26
3.3 Alcohol consumption and related factors 27
3.4 Diabetes status and related factors 27
3.5 Other diseases reported 28
3.6 Diabetic and Tuberculosis treatment and associated
factors
29
3.7 Tuberculosis disease and factors associated 30
3.8 Bivariate analysis results 31
3.9 Multivariate analysis 32
Abstract
Background
As there is evidence to suggest that in India epidemics of diabetes and tuberculosis
co-exist, it is important to study the effect of diabetes on tuberculosis treatment outcome.
Objective
To explore the association of non-cure of tuberculosis within the RNTCP program in
Kerala with diabetes and other contributory factors.
Methodology
A community based case-control study was conducted among 200 tuberculosis patients(75
failure of cure, 125 cured) selected by listing all failure cases during the year 2013,2014, and
2015 and cured patients from the same peripheral health institutions in 7 tuberculosis units in
Trivandrum district under RNTCP. Information on socio-demographic characteristics, tobacco
use, alcohol consumption, diabetes, tuberculosis, and diet related factors was collected using a
structured interview schedule. Multiple logistic regression analysis was done to find the factors
associated with failure of treatment.
Results: The percentage of diabetes among the patients was found to be 44 percent among
failures and 40 percent among cured patients. The following risk factors were identified by
simple bivariate analysis: age group >45yrs (OR 1.735, 95% CI 0.890-3.385), diabetes (OR
1.179, 95%CI 0.66-2.10),ever use of tobacco(OR 2.860, 95%CI 1.5-5.45), ever use of
alcohol(OR 2.155, 95% CI 1.179-3.939), current use of tobacco (OR 2.597, 95% CI 1.262-
5.343), current use of alcohol(OR 1.292, 95% CI 0.605-2.759), tuberculosis treatment
interruption (OR 6.469, 95% CI 2.905-14.395). Multivariate logistic regression showed that after
adjusting for confounding factors, the treatment interruption is significantly associated with
failure(Adjusted OR 3.879, 95%CI 1.510-9.965) (p, 0.005).
Conclusion: Interruption of treatment, often associated with of tobacco and alcohol use, seems
to be the strongest risk factor for treatment failure in RNTCP in Trivandrum district in Kerala.
1
Chapter 1
Introduction and review of literature
1.1 Background
Tuberculosis is one of the major public health problems in terms of communicable
diseases. India accounted for 24% of total cases in the world. The burden of disease and
death among men are so high with respect to women (WHO, 2014). The strategy beyond
2015 is “to end the epidemic of tuberculosis” with corresponding 2035 targets of a 95
percent reduction in TB deaths and a 90 percent reduction in TB incidence (both
compared with 2015). The strategy also includes a target of zero catastrophic costs for TB
affected families by 2020(WHO, 2014). Access to high quality TB care is limited by age,
gender, type of disease, social setting and the ability to pay the direct and indirect cost of
care (WHO, 2008).
When TB infection spreads inside the lungs or any other organ, 5 percent develop into
active TB disease within 5years and in those who does not develop into active TB
disease, the form of infection is called latent TB infection (LTBI). People with LTBI have
a 10% lifetime risk of developing active TB disease. Immunity is the main factor
preventing the infection from activation, multiplication and keeping it in the latent form.
Thus, any condition that impairs or weakens the immunity in the body increases the risk
of developing active TB disease by 10 percent (WHO, 2008).
The mathematical model of NTP indicates that in the absence of HIV, if 70 percent cases
detected and 85 percent of them are cured there is chance of 5-10 percent decline in
2
incidence of TB cases by coming years so if incidence decline by 5percent thereby can
achieve the MDG and Stop TB target by 2015(WHO,2008).
The most common symptom of tuberculosis is persistent productive cough, as per
RNTCP guideline a person with cough of 2weeks or more is considered as a tuberculosis
suspect. The diagnosis of tuberculosis can be confirmed by the presence of acid fast
bacilli in sputum smear microscopy; repeated sputum microscopy can detect two-third of
active disease (WHO, 2008)
1.2 Tuberculosis
a. Global Scenario
Tuberculosis (TB) remains a major public health threat around the world. In 2013, an
estimated 11 million prevalent cases (that is, the number of cases in a population at any
given time) and 9 million incident cases (that is, the number of new cases that occur in a
population in 1 year) occurred globally (WHO, 2014). Of the estimated cases, 3.3 million
were missed by health systems, either by remaining undiagnosed or by being diagnosed
but not reported (WHO, 2014). Between 2000 and 2013, an estimated 37 million lives
were saved through effective diagnosis and treatment. The six countries that stand out as
having the largest number of incident cases
in 2013 were India (2.0 million–2.3 million), China (0.9 million–1.1 million), Nigeria
(340 000−880 000), Pakistan(370 000−650 000), Indonesia (410 000−520 000) and South
Africa (410 000−520 000) (WHO,2014)
b. Indian scenario
In India the tuberculosis prevalence per lakh population was 230 in 2012(in absolute
numbers- 28 lakhs) (Government of India, 2013). India has the highest burden of TB in
the world, an estimated 2 million cases annually, accounting for approximately one fifth
of the global incidence. It is estimated that about 40% of the Indian population is infected
3
with TB Bacteria, the vast majority of whom have latent rather than active TB disease. It
is also estimated by the World Health Organization (WHO) that 300,000 people die from
TB each year in India. TB treatment in India is provided through the RNTCP and the
private sectors. Indian Govt. started the RNTCP in the year 1997 and expanded it
throughout the country by March 2006. The programme uses WHO recommended DOTS
Strategy in 632 districts. The data collected from a cross sectional study in India with
609 patients reveal that only 54%(CI 42-66%) received treatment through RNTCP while
278 (46%) (CI 34-57%) patients received treatment from private sector (Satyanarayana et
al, 2011). There is growing evidence, from national TB prevalence surveys and other
researches, of a large pool of undetected TB in the community (Lonnroth K et al, 2013).
In India, the case detection rate doesn't indicate much difference from 1995-
2013, it ranges between 58-61%. The cohort size increased from 2, 65,000 in 1995 to 14,
67,585 in 2013, among that sputum positive comes to about 9,33,905(Govt of
India,2013). Eight tuberculosis suspects have to be examined for one sputum positive
case to get diagnosed.
c. Kerala
The prevalence of tuberculosis in south India including Kerala by National ARTI survey
done by Central TB Division in the year 2009-10 is 6.8 percent, which is higher than 6.1
at 2000-01 and annual risk of tuberculosis infection (ARTI) in Kerala is <1percent (TB
India, 2013). For the State of Kerala, the ratio of the number of new smear negative to new
smear positive cases varies in the range 0.5 to 0 .7 where as for all India the ratio was in the
range of 0.7 to 0.9(Subramanya Rao, 2004). The new smear positive cases per lakh
population based on ARTI in Kerala is 50, lowest when compare to other Indian states. In the
year 2012, a total of 25,917 cases being registered, in that the sputum positive cases comes
to about 15,182 (59percent of total cases notified by the system (TBIndia,2013). In Kerala the
tuberculosis suspect cases required to be examined for a smear positive case to be
4
diagnosed is 24(Government of India, 2013), highest in the country. In Kerala the three
month sputum conversion rate is 88percent which is less than the National average of 90
percent. But the composite indicators which is formulated to assess the the performance of
the programme in each state shows a case finding effort of only 48percent in
Kerala(Government of India,2013), which needs improvement. Among the 10,747 sputum
positive cases registered in 2011, treatment failure occurred for 5percent cases.
1.3 RNTCP (Revised National Tuberculosis Control Programme)(TB India, 2012)
The Revised National TB Control Programme (RNTCP), based on the internationally
recommended Directly Observed Treatment Short-course (DOTS) strategy, which was launched
in 1997, expanded across the country in a phased manner with support from the World Bank and
other development partners. RNTCP has achieved the NSP case detection rate of more than 70%
and the treatment success rate of >85% in 2007 and is persistently maintaining these global
targets for TB control since then. Annually more than 1.5 million TB patients are placed on
DOTS treatment under RNTCP. The program has been covering the entire nation since March
2006; reaching over a billion population (1164 million) in 632 districts/reporting units. The
program is focusing on the reduction in the default rates among all new and retreatment cases and
is undertaking steps for the same. The rate of TB Suspects examined has increased substantially
from 397 per 100000 population per annum to 652 per 100000 population over the last 10 years.
The programme had revised its categorization of patients from the earlier 3 categories (Cat I, Cat
II and Cat III) to 2 categories (New and Previously treated cases) based on the recommendations
of experts and endorsement by National Task Force for Medical colleges.
Drug Resistance Surveillance (DRS) of Gujarat, Maharashtra and Andhra Pradesh, estimated the
prevalence of Multidrug Resistant TB (MDR-TB) to be about 2-3% in new cases and 12-17% in
retreatment cases.
Impact of the programme: TB mortality in the country has reduced from over 39 per hundred
Thousand populations in 1990 to 29 hundred thousand population in 2010 as per the WHO Global
TB Report 2011.
5
12th Five Year Plan: RNTCP has developed National Strategic Plan to be implemented during
2012-2017, the national 12th Five Year plan period, with following Vision for RNTCP.
Vision: "TB-free India"
1.4 Global Goals, targets and indicators for TB control
Millennium Development Goals set for 2015
Goal 6: Combat HIV/AIDS, malaria and other diseases
Target 6c: Halt and begin to reverse the incidence of malaria and other major diseases
Indicator 6.9: Incidence, prevalence and death rates associated with TB
Indicator 6.10: Proportion of TB cases detected and cured under DOTS
Stop TB Partnership targets set for 2015 and 2050
By 2015: Reduce prevalence and death rates by 50%, compared with their levels in 1990
By 2050: Reduce the global incidence of active TB cases to <1 case per 1 million
population per year.
1.6 NPCDCS (National Programme for control and prevention of Cancer, Diabetes,
Cardiovascular disease, and Stroke)
Pilot phase of the National Programme for Prevention and Control of Diabetes,
Cardiovascular Diseases and Stroke (NPDCS) launched on 4th Jan 2008, later renamed
including cancer as NPCDCS. In the program, it is envisaged in providing preventive,
promotive, curative, and supportive services (core and integrated services) for Cancer,
Diabetes, Cardio-Vascular Diseases (CVD) and Stroke at various government health
facilities with provisions for expanding the diseases covered under the program to chronic
lung diseases, geriatric diseases, etc. The package of services would depend on the level
of health facility and may vary from facility to facility. The range of services will include
health promotion, psycho-social counseling, management (out-and-in-patient), day care
services, home-based care, and palliative care as well as referral for specialized services
6
as needed. Linkages of District Hospitals to private laboratories and NGOs will help to
provide the additional components of continuum of care and support for outreach
services. The district will be linked to tertiary cancer care health facilities for providing
comprehensive care.
Health education program that promotes exercise, weight reduction, screening, and early
diagnosis are some of the key interventions that need to be promoted at various levels of
heath facilities (Krishnan et al., 2011).
1.7 Socio economic and demographic factors influencing TB
a. Age- According to WHO, 2014, the age group of most TB cases were above 15yrs,
<15yrs accounts for only 6 percent of notifications. In Western pacific Region there is
progressive increase in notification rate with age and the peak being ≥65yrs old. A
similar pattern in East Mediterranean Region, to a lesser extent in South East Asia
Region, elsewhere the peak age is young adults. In Asia, there is a progressive increase in
the prevalence of TB with age. As transmission declines, levels of infection in younger
age groups fall and the burden of disease shifts to older age groups. This is reinforced by
the demographic transition in these countries, which is associated with a general ageing of
the population. The age distribution of cases in Africa is more mixed, with some countries
(e.g. Gambia, Rwanda) having a pattern similar to that observed in Asia and others (e.g.
Ethiopia, Nigeria) having a peak prevalence in younger age groups.(WHO,2014)
There is no increase in age standardized diabetes prevalence in East and South
East Asia (Danei et al, 2011). In developing countries, the majority of people with
diabetes are in the 45- to 64-year age range. In contrast, the majority of people with
diabetes in developed countries are 64 years of age. By 2030, it is estimated that the
number of people with diabetes at 64 years of age will be 82 million in developing
countries and 48 million in developed countries (Wild et al, 2004)
7
b. Sex - The risk of developing TB with age after puberty particularly among men is high,
and males have both a higher rate of infection and a higher risk of progression to active
TB disease over the course of their lives than women (WHO, 2008). Prevalence is much
higher among men than women. The sex ratio (M: F) is typically between 2:1 and 3:1 in
Asia. In Africa, more cases also occur among men (WHO,2014). The male female sex
ratio of TB cases was 1.6 globally, but among HBCs this ratio varied from 0.7 in
Afghanistan to 2.9 in Viet Nam. The variation may be real difference in epidemiology as
well as differential access to/use of health service linked to NTP (WHO, 2014).
The age standardized adult diabetes prevalence was 9.8 percent in men
(8.6-11.2) and 9.2 percent (8-10.5) in women, in 2008(Danei et al, 2011).
C.Education- In India the literacy rate according to 2011 census data is 74.04percent
which is 9.21 percent higher than in 2001. In Kerala the literacy rate by 2011 census is
93.91percent(UNESCO,2014).
D. Employment- Employment and working conditions have powerful effects on health
and health equity. When these are good they can provide financial security, social status,
personal development, social relations and self-esteem, and protection from physical and
psychosocial hazards – each important for health. A number of employment-related
conditions are associated with poorer health status, including unemployment and
precarious work – such as informal work, temporary work, contract work, child labor, and
slavery/bonded labor (WHO-SDH, 2013)
e. House hold conditions- The number persons in home, and number of room
proportionately with that is overcrowding and poor housing are driving forces of TB
epidemic (WHO, 2008). Urbanization tends to push up TB incidence in India because the
annual risk of infection has been found to be 69% higher in urban than rural areas (WHO-
SDH, 2014).
8
1.8 BMI- The number of new TB cases in India have increased by 28% from 1.78 million
in 1998 to 2.10 million in 2008 faster than the population growth(22%), because of
adverse effect of changing BMI, rising diabetic prevalence, urbanization and ageing(Dye
C et al.,2011),so there is exponential growth in case load, at least in the short term, this is
a significant penalty for relaxing TB control only by chemotherapy(Dye C et al,2011).
1.9 Alcohol consumption- The NSSO‟s 2011-12 consumption data splits per
capita weekly consumption of alcohol into four categories – toddy, country liquor, beer
and foreign/ refined liquor or wine. The average rural Indian drinks 220 ml across types
of alcohol in a week or 11.4 liters in a year. Toddy is the most popular drink for rural
India followed by country liquor. The average urban Indian, meanwhile, drinks 96 ml per
week or 5 liters in a year, country liquor being most popular. It was also revealed that
over 11percent of the population in India indulged in heavy/binge drinking. The global
figure stood at 16percent. On the „Years of Life Lost‟ scale, which is based on alcohol-
attributable years of life lost, India has been rated 4 on a scale of one to five . This implies
that the alcohol consuming population of our country loses most years of life because of
drinking and its consequences. Alcohol consumption also contributes to about 10 percent
of the disease burden due to epilepsy, tuberculosis, hemorrhagic stroke and hypertension
in the world (WHO Global Report, 2014)
In one study for demonstrating the potentiation of plasma Insulin response to glucose, by
prior administration of alcohol showed that, ethyl alcohol seemed to modify the β cell
function, indicated by the plasma insulin response to glucose loading after prior
administration of alcohol. Other effects of alcohol included blunting of the plasma
pyruvate and exaggeration of plasma lactate elevations after glucose (Metz R et al, 1969).
From a study done at 14 high burden countries the dose response relation between alcohol
9
consumption and self reported symptoms of active TB disease by gender shows the trend
below (straight line-male , dotted line-female)..
The drinking amount shows a steeper dose response relation with TB symptoms (PatraJ et
al, 2014). The alcohol induced disorders affect TB disease progression in settings of
medication non-adherence, change in TB medication pharmacokinetics, default from TB
programme and poor treatment outcome (Patra J et al, 2014).
Figure 1 source: Patra J et al
10
1.10 Tobacco usage- National Family Health Survey (NFHS-3) of 2005-06 found that
tobacco use was more prevalent among men than women in the reproductive age of 15-49
years. Prevalence of tobacco use was found in 57 percent of men (urban: 49.9 percent,
rural: 61.1 percent) and in 10.9 percent of women (urban: 6.7 percent, rural: 12.9
percent).Studies shows that the smoking amount and smoking duration showed a strong
dose response relationship in women, than in men. The self reported symptoms of TB
were seen in men and especially in women for 21 or more years of smoking or 21 or more
cigarettes per day (Patra J et al, 2014). Smoking has been identified as a possible risk
factor for Insulin resistance; it also deteriorates the glucose metabolism leading to onset
of type2 diabetes. Smoking related risk of diabetes increases with the number of
cigarettes smoked (ASH, 2012). The cancer prevention study 1, found that women who
smoke more than 40 cigarettes per day have a 74 percent increased risk of developing
diabetes, while that of men were 45 percent (Will JC et al, 2001). Passive smoking is also
associated with increased risk of diabetes; it is evident from the CARDIA study in 2006.
Smoking is associated with multiple complications of diabetes: nephropathy, neuropathy
and retinopathy being the common complications (Ritz E et al, 1996). A large prospective
study of US nurses found that among those with diabetes the relative risks of mortality
were 1.31 for past smokers, 1.43 for current smokers of 1-14 cigarettes per day, 1.64 for
smokers of 15-34 cigarettes per day, and 2.19 for current smokers of 35 or more
cigarettes per day (Al-Delaimy et al, 2001).
1.11 Diabetes- Considerable evidence demonstrates that diabetes increases susceptibility
to Mycobacterium tuberculosis infection and the development of tuberculosis. Research
in animal models has demonstrated that mice with diabetes that were experimentally
infected with M. tuberculosis had higher bacterial loads compared to euglycaemic mice,
regardless of the route of inoculation, a direct adverse effect of acute hyperglycemia. This
11
suggests that the impaired host defense is a consequence of persistent hyperglycemia
(MartensGM, 2007). Compared to euglycaemic mice, chronically diabetic mice also had a
significantly lower production of interferon-gamma and interleukin-12 and fewer M.
tuberculosis antigen-responsive T cells in the early course of M. tuberculosis infection,
marking a diminished T helper-1 adaptive immunity, which plays a role in controlling
tuberculosis infection (Gregory W. Martens, 2007). Leukocyte bactericidal activity is
diminished in people with diabetes mellitus, especially those with poor glucose control.
Diabetic patients had more symptoms associated with tuberculosis infection than those
without (Alisjahbana B, 2007). Neutrophils from people with tuberculosis and diabetes
mellitus had reduced chemotaxis and oxidative-killing potential, compared to that in non-
diabetic controls (Delamaire M,, 1997). This demonstrates a dose-response relationship
between the degree of hyperglycemia and vulnerability to tuberculosis (Reid MGA,
2013). Autonomic neuropathy could play a role in decreasing the ability of patients with
diabetes to clear the bacterial load, as well as impairing their capacity to combat the
tuberculosis pathogen ( Kapur A, 2013). In 1935 tuberculosis was declared one of the
four commonest causes of death in patients, along with diabetes mellitus ( Flynn
JM,1935). Before the introduction of insulin it was estimated that infections especially
tuberculosis killed 20% of the diabetic patients (Warrel DA, 2010).
The global prevalence of diabetes (defined as a fasting plasma glucose value ≥7.0
mmol/L [126 mg/dl] or being on medication for raised blood glucose) was estimated to be
9% in 2014(Global status report on NCD, 2014)387 million people have diabetes; by
2035 this will rise by 592 million. 77% of the people with diabetes live in low-and
middle-income countries. 179 million people with diabetes are undiagnosed (WHO,
2014). Diabetes was directly responsible for 1.5 million deaths and 89 million DALYs in
2012 (WHO, 2014).
12
The severity of the global challenge of co-epidemic of tuberculosis and diabetes became
recognized with reports of a threefold increase in active TB associated with diabetes
(Jeon et al., 2008). Diabetes may be responsible for more than 10% of tuberculosis cases
in countries such as India and China, a figure that will likely increase as diabetes becomes
more common (Jeon et al 2008). A cross sectional study among Ethiopian patients
showed that the prevalence of smear positive PTB was 6.2% in TB suspected diabetic
patients, which was higher compared with the general population (0.39%) (Hiwot Amare,
2013). The countries with high prevalence of diabetes also show a high prevalence of
tuberculosis. So there is a chance of an epidemic of diabetes and tuberculosis (IDF,
2013). In 10 case control studies, the pooled odds ratio of TB among DM cases was 2.2
(ranged from 1.16 to 7.81) and in 4 cohort studies pooled relative risk was 2.52 (95% CI:
1.53 to 4.03) (IUATLD, 2011). The degree of this effect can be influenced by factors
such as age, DM type, severity of DM, prevalence of TB in the region, and ethnicity.
In one study in India ICMR-INDIAB STUDY, more than 62
million diabetic individuals currently diagnosed with diabetes (JoshiSR, 2007). It is
predicted that by 2030 diabetes mellitus may afflict upto 79.4 million individuals in India,
while China (42.3 million) and the United states (30.3 million) (Wild et al, 2004). India
currently faces an uncertain future in relation to the potential burden that diabetes may
impose upon the country. There are patterns of diabetes incidence that are related to the
geographic distribution of diabetes in India. ICMR study revealed lower proportion
affected in states of North India (.12 million in Chandigarh, 0.96 million in Jharkand) as
compared to Maharashtra (9.2 million), Tamil nadu (4.2 million). National Urban Survey
across metropolitan cities reported similar trend, 11.7% in Kolkata, 6.1% in Kashmir
Valley, 11.6% in New Delhi, 9.3% in Mumbai, 16.6% in Chennai, 13.5% , 16.6% in
13
Hyderabad(south India), and 12.4 per cent Bangalore (South India) (Seema Abhijeet,
2014). Modeling has suggested that diabetes accounts for 14.8% of all tuberculosis and
20.8% of smear-positive TB in India (Government of India, 2013).
DM is common in the south Indian state of Kerala (population34.6 million), with an
estimated community prevalence of 16% to 20% (Kutty VR, 1999) (Menon VU, 2006).
The diabetes prevalence among tuberculosis patients in Kerala is found to be 44 percent
(95% CI 38.8–49.3) ( Balakrishnan et al, 2012), which is higher than general population. .
Insulin use is only 2-10% (Menon VU et al, 2008) among the diabetics.
14
1.12 Glycemic control- It is well known that acute infection leads to difficulty in
controlling the blood sugar levels and that infection is the most frequent cause of
ketoacidosis (Eliot j et al, 1982). In a population based case-control study done in
Denmark, diabetic individuals with an HbA1c <7, 7-7.9, and ≥ 8 percent had OR of
0.91(0.51-1.63), 1.05(0.41-2.66) and 1.19(0.61-2.30) respectively compared with
individuals without diabetes for tuberculosis. Optimal glycemic control might improve
better outcomes of tuberculosis treatment and prevent many of the complications.
Tuberculosis leads to decrease in appetite, bodyweight, and physical activity, which
might affect glucose homeostasis. Inflammation associated with TB could cause Insulin
resistance and good glycemic control is dependent on the quality of health care system
Figure 2 source Riza AL et al.
15
(Riza AL, 2014). The baseline data of A1c heive study in 20,554 Indians showed that
the mean HbA1c was 9.2% .
Diabetes control was worse in those with long duration of diabetes (9.9+/- 5.5yrs).
The use of Insulin was suboptimal owing to clinical inertia. The chance of complications
is common in patients with poor glycemic control (MohanV, 2013).
1.12 Tuberculosis treatment related factors
Th standardized regimens for treatment of tuberculosis recommended by WHO include
five essential medicines designated as first line includes, isoniazid(INH), Rifampicin(R),
pyrazinamide(P), Ethambutol(E), and streptomycin(S)(WHO,2008 pageno.25). The
pharmacokinetic aspects of TB treatment, the available evidence suggests that the
efficacy of rifampicin is dependent on exposure to the drug or on the maximum drug
concentrations achieved (Jayaram R, 2003). The inadequate management of adverse
effects is likely to contribute to the irregular treatment and default. So the WHO
suggesting pharmacovigilance system in NTPs(National TB programmes)(WHO,2008).
There should be access to care, support for the patient, and reducing their hardships by
the health system to ensure proper and complete treatment(WHO,2008) The exposure
(area under the curve, 0–6 h) to rifampicin was 2-fold lower in patients with TB who had
DM than in patients who did not have DM (Nijiland HM, 2006). Similar differences were
found for the maximal plasma concentrations of rifampicin; the maximal plasma
concentration of rifampicin was above the target concentration of 8 mg/L (Peloquin,
2002) in 6% of patients with TB who had DM, compared with 47% of patients who did
not have DM. These pharmacokinetic differences might lead to easier acquisition of drug
resistance and might explain the lower bacteriological response in diabetic patients with
TB.
16
1.13 Rationale of the study
In Kerala, most of the health and socioeconomic indicators are higher than the National
level. It is also witnessing high prevalence of diabetes among general population (16-
20%), and low level of tuberculosis case load when compare to the rest of India. It is also
noted that among the notified tuberculosis cases the percentage of people with diabetes is
found to be the highest (40-44%) when compared to rest of India. The percapita
consumption of alcohol and tobacco use is also high in this state. In these circumstances
the study regarding the treatment outcome of RNTCP patients is utmost important to
enabling effective care of the persons affected with the diseases.
Kerala should adopt strategies separately to curtail the chain of transmission of
infection. To the best of my knowledge there is hardly any literature detailing the
association of non-cure of tuberculosis and diabetes in Kerala.
1.14 Research questions
1. Is there any association between diabetes and tuberculosis noncure?
2. What were the other factors contributing noncure?
1.15 Objectives
a. Major objective:
To explore the association between noncure of tuberculosis in
patients in
RNTCP programme and prevalence and control of diabetes in them.
b. Minor objectives
To explore other factors associated with noncure.
17
Chapter 2
Methodology
2.1 Study Type
It was a community based case-control study.
2.2 Study setting
The study was conducted in 7 tuberculosis units including 65 peripheral health institutions
(PHUs) under RNTCP in Trivandrum District.
2.3 Study population
The study population was patients who were diagnosed with tuberculosis for the first time in
the years 2013, 2014, and first quarter of 2015 and who had taken one full course of
treatment, and were willing to participate in the study.
2.4 Time frame
Data were collected during the period of June 25, 2015 to September 15, 2015
2.5 Sample size
Sample size was estimated using OpenEpi, Version 3, with the assumption that controls
exposed to diabetes will be 20 percent and cases exposed to diabetes will be 40 percent, 95%
18
confidence level, and 80 percent power. The estimated sample size came to 182 (91 each).
Considering 5 percent dropout rate and rounding it up, the study sample size was fixed 200.
2.6 Criteria
Inclusion
- The tuberculosis patients whose outcome was declared either cured or noncured
Exclusion
- The patients whose treatment started in a particular tuberculosis unit and were
transferred out to other district during treatment
2.7 Sample selection procedure
Subjects were selected according to the following routine:
(a)A Tuberculosis unit wise list was prepared of all the non cured (treatment failure) patients
in the year 2013, 2014 and 2015 till the time of study, because diabetes screening was
initiated during this periods.
(b)A separate Tuberculosis unit wise list of cured patients during the period from the same
peripheral health institution (of failures) were prepared.
The patients were visited in their home; some times more than single visit was require. In
rare situations they were called to the nearby peripheral health institution. As the patients
were spread throughout the district experienced data collectors were identified and given
training and used for house visit and data collection. Non cured patients – cases- were 104 in
the list but during house visit it was understood that 7 persons had died, 6 persons defaulted
19
during the second phase of treatment and some of the patients changed their residence so
finally we were restricted to 75 cases. We identified 125 controls (cured cases from the same
cohort) so that the total estimated sample size was not disturbed.
2.8 Method of data collection
Structured interview schedule developed by the PI (Principle Investigator) and translated
into local language was used to collect the information. The interview schedule had ten
sections, viz.,.sociodemographic profile, pattern of tobacco use, pattern of alcohol
consumption, self reported physical measurements, blood pressure measurement done during
treatment, diabetes and its treatment related questions, other diseases related questions,
tuberculosis and its treatment related questions, and diet related questions.
2.9 Data cleaning
At the first step, all the data sheets were checked manually for any mismatches and corrected
accordingly. Later the data were cleaned using computerized cleaning process.
2.10 Data storage
Along with data collection the data were entered into Excel sheet and rechecked for
validation. Later data were imported to SPSS software, version 21 for analysis. The hard
copies of the filled interview schedules and consent forms are kept in the locked chamber
under the custody of the PI. The privacy and confidentiality of the study participants are
being strictly maintained.
20
2.11 Data analysis and statistical methods
Analysis was done using SPSS software version 21 to study the sample characteristics, risk
factors associated with tuberculosis, treatment related factors for failure of treatment and diet
related factors. Bivariate analysis was done with outcome variable which indicated case-
control status, i.e., failure and cure. Statistical tests were also done for all the tests, p-value of
<0.05 was considered as significant. For adjustment of possible interaction and confounding
factors, multiple logistic regression analysis was performed to arrive at a final model. The
predictor variables that had p-value ≤0.1 and diabetes factor were considered for multiple
logistic regression analysis. The effect of different predictor variables was explained in terms
of odds ratio (OR) with 95% of confidence interval (CI).
2.12 Study variables
Below are the study variables taken in the study.
a. Outcome variables
1. Failure (cases): Those who were diagnosed to have sputum positive tuberculosis for the
first time and registered in a particular tuberculosis unit, taken treatment full course as per
RNTCP guideline, at the end of the regime declared failed of treatment.
2. Cure (controls): Those who were diagnosed to have sputum positive tuberculosis for the
first time and registered in a particular tuberculosis unit, and taken treatment as per the
RNTCP guideline, at the end of the regime declared cured.
21
b.Predictor variables
Initially the predictor variables were grouped into a number of groups, for example the
highest level of education was grouped as no formal schooling, primary, high school(HS)
completed, higher secondary(HSS) completed, degree completed, postgraduate(PG)
completed. But during analysis these were regrouped into three groups as no schooling,
primary and HS, HSS, degree, and PG in one group. Similarly for other variables regrouping
was also done. Our interview schedule included the following predictor variables.
1. Marital status: Regrouped as married and unmarried
2. Current age: Based on the sample characteristics it was regrouped as ≤45 years and
>45years
3. Current occupation: Regrouped as employed and unemployed
4. Persons staying together: Regrouped as ≤3persons and 4-6persons, and >7 persons.
5. Number of rooms in home: Regrouped as ≤3 rooms, 4-6 rooms, and >6rooms
6. Physical measurements: weight and height at time of treatment that were recorded in
the identity card were recorded.
7. Family history of diabetes: diabetes among blood relatives and among spouse.
8. Treatment for cough in the beginning: Regrouped as self medication, govt., and
private hospital.
9. Duration of diabetes: Regrouped as <5yrs, 5-10yrs, and >10yrs.
10. The reason for tuberculosis treatment interruption: Regrouped as related to the adverse
effect of drug and other personal reason.
22
In addition data related to tobacco use, alcohol consumption, diabetic and tuberculosis
treatment related, diet was also recorded.
2.13 Ethical consideration
The study obtained clearance from the Technical Advisory Committee (TAC) and IEC of
Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram,
Kerala. Prior to data collection, the study had also obtained permission from the Department
Of Health and Family Welfare, Government of Kerala. This study complied with the basic
Ethical principles of research. Written informed consent (Annexure 3) for participating in the
study was taken. Consent form had also research subject information sheet containing the
information about the study, and the contact details of principal investigator. It was translated
into local language. One copy of the signed informed consent form that included research
subject information sheet was handed over to the participants. In case of illiterate study
participants, research subject information sheet was explained to participants before taking
their thumb impressions and the same was witnessed by another literate person. Participants
had full freedom of either accepting or refusing to participate, and for withdrawing
participation at any time of the study without any explanation and consequences.
Respondents were informed regarding the voluntary nature of participation, study objectives,
and the potential benefits and risks of participation. Utmost ease was given to protect the
privacy and confidentiality of the participants. Personal information of the participants was
not shared with anyone not involved in the study. The TB number was used to maintain the
confidentiality. They were also given chance to ask any question, query or doubt related to
the study.
23
Chapter 3
Results
The findings of the study are presented in this section. The general description of the study
population is presented first. Analysis of the factors associated with noncure of tuberculosis is
described under the two subsections bivariate analysis and multiple logistic regression
analysis.
3.1: Sample Characteristics
A detailed depiction of the study has been given in this section. Subject characteristics
assessed were socio-demographic details, tobacco use, alcohol consumption, diabetes status
and treatment details, details regarding other disease, tuberculosis disease and treatment
details, HIV status, as well as diet related characteristics for cases and controls separately.
3.1.1 Socio-demographic factors:
The background characteristics of the study participants are explained in Table 3.1 The
data were from 75 cases (failures) and 125 controls (cured) following initiation of DOTS
therapy. The mean age of cases was 54.68±11.84, that of controls being 51.58±15.6. The data
shows that females constitute only 18% of the total. When we see the age group wise data,
we can see that >70% of subjects in both cases and controls groups were above 45yrs.
Unemployed persons include 42% of the total. Out of 36 women, 22 are unemployed. The
employed means any type of job, private job, govt. job, self employment, business& house
maid. There is not much difference between cases and controls with respect to employment,
schooling, and marital status. The monthly income of majority of the patients are less than
5000RS (75% of cases) indicating low income groups are more affected than high income
group.
24
Table 3.1: Socio-demographic details
*BPL-Below poverty line **APL- Above poverty line *#HSS-Higher secondary school
Cases No.(%)(N=75)
Controls No.(%)(N=125)
Age
Mean age 54.68 51.58
Standard deviation 11.84 15.6
<=45yrs 16(21) 40(33)
>45yrs 59(79) 85(67)
Sex
Male 66(88) 98(78)
Female 9(12) 27(22)
Level of Education
No schooling 11(15) 20(16)
Primary, High school 55(73) 81(65)
HSS*#, Degree, PG 9(12) 24(19)
Marital status
Married 71(95) 113(90)
Unmarried 4(5) 12(10)
Current Occupation
Employed 47(63) 70(56)
Unemployed 28(37) 54(43)
Monthly Income(R.S)
<5000 56(75) 78(62)
5000-10000 12(16) 37(30)
>10000 7(9) 10(8)
Type of Ration card
(BPL)* 44(59) 62(50)
(APL)** 31(41)
63(50)
Religion
Hindu 54(72) 93(74)
Muslim 11(15) 12(10)
Christians 10(13) 20(16)
The study shows about 59 percent of failures belongs to BPL category, and above 70
percent of both groups belong to Hindu religion. There is no significant difference between
both cases and controls in socio demographic factors, so the socidemographic factors are
not significantly influencing the outcome of tuberculosis treatment.
25
Table 3.1b Socio-demographic profile(2)
Cases No. (%) Controls No. (%)
Type of House
Thatched Roof&Mud floor 15(20) 23(18)
Sheet roof&cement floor 5(7) 6(5)
Concrete House 26(35) 47(38)
Tiled Roof &Cement floor 29(38) 48(38)
No. of rooms in home*
<3rooms 58(77) 98(78)
4-6rooms 17(23) 25(20)
>7rooms nil 2(2%)
Persons staying with#
<3persons 24(32) 37(30)
4-6persons 42(56) 78(62)
>6persons 9(12) 10(8)
*The mean number of rooms in a home,3 with range(1-7), # the mean number of
persons staying with 5 with range (1-17).
The type of house, numbers of rooms in home and number of persons staying with are important in
tuberculosis. But these factors are not found to be associated with noncure of tuberculosis..
3.1.2 Tobacco and related factors
The data shows about 77percent of cases and 54percent of controls had history of smoking;
OR 2.86(CI 1.5-5.45), p-value 0.001, and among this 59percent of cases and 35percent of
controls are current smokers OR 2.6(CI 1.26-5.34) p-value 0.009. Among failures 45percent
are daily smokers, and among cured subjects 26percent are daily smokers. The mean age of
initiation of smoking is 19yrs with ranges from (9-40yrs). The smoking cessation was tried
by around 80 percent of subjects. Pan chewing history is shown by 23 percent of failure
subjects and 17 percent of cured subjects.
26
Table 3.2: Tobacco use and related factors
Cases No. (%) Controls No. (%)
Ever smoked
Yes 58(77) 68(54)
No 17(23) 57(46)
Current smoke
Yes 34(58) 24(35)
No 24(42) 44(65)
Daily smoking
Yes 26(45) 18(26)
No 32(55) 50(74)
Age of starting smoking
<18yrs 28(55) 27(47)
18-25yrs
18(35) 25(43)
>25yrs 5(10) 6(10)
Tried for smoking cessation
Yes 47(81) 53(78)
No 11(19) 15(22)
Passive smoking 11(15) 10(8)
Ever pan chewing 17(23)
21(17)
3.1.3: Alcohol Consumption
The table shows the last yrs consumption has been reduced to 60-65%
after diagnosis of tuberculosis for both cases and controls, but 46percent failure(noncure)
subjects seems to be continuing the daily consumption. The mean number of days consuming
alcohol (9±8.9) ranges from 1-30 days/month. 16-18 percent of subjects initiated alcohol
consumption below the age of 18years.
27
Table 3.3: Alcohol consumption and related factors
Cases No. (%) Controls No. (%)
Ever consumed alcohol
Yes 52(69) 64(51)
No 23(31) 61(49)
Last yrs consumption
Yes 34(65) 38(59)
No 18(35) 26(41)
Age of initiation
<18yrs 7(16) 9(18)
18-25yrs 15(35) 15(31)
>25yrs 21(49) 27(55)
Current consumption
Yes 24(46) 21(38)
No 28(54) 43(62)
3.1.4: Diabetes status and related factors
Diabetes mellitus seems to be a risk factor for tuberculosis as 40percent of all patients are
diabetic, and more than 90 percent of the patients had a history of less than 10 years’
duration of diabetes. The mean PPBS is found to be 237±70mg/dl among failures and
233±71mg/dl among cured subjects, with range of (106-400mg/dl). The mean duration of
diabetes 6±4.9yrs; with ranges (1-25yrs). About 22 percent diabetes subjects had family
history of diabetes.
Table 3.4: Diabetes status and related factors
Cases No.(%)(N=75) Controls
No.(%)(N=125)
Diagnosed diabetes
Yes 33(44) 50(40)
No 42(56) 75(60)
Duration of diabetes
<5yrs 23(70) 30(60)
5-10yrs 7(21) 13(26)
>10yrs 3(9) 7(14)
PPBS reported* 237±70mg/dl 233±71mg/dl
*33 cases and 42 controls reported PPBS(post prandial blood sugar)
28
3.1.5: Other diseases
The data shows about 24% of cases and 27% of controls had history of other diseases. This
includes CVD (coronary vascular disease), hypertension, asthma, pancreatic calculi*, Ca
oropharynx*, malnutrition*, hepatitis*, dyslipedemia*.
Table 3.5: Other diseases reported
Cases N0.(%)(N=75) Control No.(%)(N=125)
Coronary vascular diseases 4(5) 11(8)
Asthma 6(8) 10(8)
Hypertension 15(20) 20(16)
*one each
3.1.6: Diabetes and Tuberculosis treatment and associated factors
The data show only 14-15% of diabetics are on adequate treatment for diabetes, rest of them
either take single dose of Insulin or tablet irrespective of their blood sugar status. The history
of diabetes treatment interruption is less among diabetics, (18percent of cases and 4 percent
of controls). All patients follow DOTS (Directly Observed Treatment Short course) regime.
The medicines are available from the approved DOT centers, which are arranged near the
patient’s residence so that treatment will not get interrupted. The tuberculosis treatment part
is concerned, 36 percent of non cured subjects had history of interruption OR6.47(2.91-
14.40), p-value <0.0001, in this 78 percent had reason for interruption as the treatment related
adverse events like discomfort, vomiting, abdominal pain etc.
29
Table 3.6 Diabetic & Tuberculosis treatment and associated factors
Cases No.(%)N=75 Controls No. (%)
N=125
Patients taking regular
treatment for diabetes
(DM=33) (DM=50)
Yes 28(37) 47(38)
No 47(73) 78(62)
The health sector from where
treatment for diabetes
Government 21(75) 38(81)
Private 7(25) 9(19)
Insulin only
Yes 15(54) 17(36)
Tablet only
Yes 9(32) 21(45)
Insulin+Tablet
Yes 4(14) 9(19)
History of DM** treatment
interruption
Yes 5(18) 2(4)
Whether TB treatment
interrupted
( N=75) (N=125)
Yes 27(36) 10(8)
Reason for interruption
Related to treatment* 21(78) 8(80)
Other personal reason# 6(22) 2(20)
*includes vomiting, abdominal discomfort, admission at hospital, hepatitis etc.
#includes tour for livelihood, sister died, out os station for other reasons
**DM-diabetes mellitus.
3.1.7: Tuberculosis disease related factors
The duration of cough till the diagnosis of tuberculosis can influence the outcome of the
DOTS Treatment. The duration of cough is more important, as delay in diagnosis of a single
sputum positive case can cause spread of infection to 10-15 persons at a time. The family
history of tuberculosis is 7-8 percent. 77percent of both groups had taken treatment for cough
from government hospital. The diagnosis of 20 percent done within one week duration of
30
cough and 40 to 50 percent took more than one month to get diagnosed of tuberculosis.
Almost 92 percent of failure’s sputum got cultured for the diagnosis of MDR, and one subject
diagnosed to have MDR. The accredited social health activist (ASHA) provided DOTS for
around 20 percent of the subjects, majority took DOTS from hospital. The study shows
almost 20 percent and above subjects took DOTS from DOT center which is situated more
than one kilometer distance. All subjects tested for HIV, only person in control group came to
positive and got cured.
Table 3.7: Tuberculosis disease and factors associated
Cases No. (%) N=75 Controls N0. (%) N=125
Treatment taken for
cough before TB diagnosis
Govt. Hospital 58(77) 96(77)
Pvt. Hospital 12(16) 27(22)
Self medication 5(7) 2(1)
For how long treatment
taken
<Week 15(20) 29(23)
1Week-1Month 22(29) 47(37)
>1month 38(51) 49(39)
Tuberculosis diagnosed from
Govt. Hospital 71(95) 121(97)
Pvt. Hospital 4(5) 4(3)
Family history of
tuberculosis
Yes 6(8) 9(7)
Sputum culture done
Yes 69(92) 33(26)
Culture result
Negative for MDR* 67(97) 33(100)
Positive for MDR 1(1.5)
NTM** 1(1.5)
Dot Centre/Provider
ASHA# 13(18) 30(24)
Anganwadi 15(20) 17(14)
Hospital 39(52) 59(47)
Social worker 7(10) 19(15)
Distance between home and
DOT centre
<500m 41(54) 77(62)
500m-1Km 17(23) 16(13)
>1Km 17(23) 32(25)
*MDR-multidrug resistant tuberculosis, **NTM-Non tuberculous mycobacterium
#ASHA-Accredited social health activist
31
3.2: Results of Bivariate Analysis
Simple Chi-square analysis and binary logistic regression analysis was
performed to examine the possible association between the predictor variables and the
outcome variables. The outcome variables here are the tuberculosis treatment failure and
cure.
Cases No(
%)
Controls
No(%)
Unadjusted Odds
Ratio(CI**)
P_value
Sex Male 66(88) 98(78) 1
Female 9(12) 27(22) 2.02(0.89-4.57) 0.087
Age ≤45 16(21) 40(32) 1
>45 59(79) 85(68) 1.74(0.89-3.39) 0.104
Diagnosed diabetes Yes 33(44) 50(40) 1
No 42(56) 75(60) 1.18(0.66-2.10) 0.578
Ever smoked Yes 58(77) 68(54) 1
No
17(23) 57(46) 2.86(1.50-5.45) 0.001*
Current smoke Yes 34(59) 24(35) 1
No 24(41) 44(65) 2.60(1.26-5.34) 0.009*
Ever consumed
alcohol
Yes 52(69) 64(51) 1
No 23(31) 61(49) 2.16(1.18-3.94) 0.013*
Current
consumption
Yes 24(71) 21(55) 1
No 10(29) 17(45) 1.29(0.61-2.76) 0.507
Whether TB
treatment
interrupted
Yes 27(36) 10(8) 1
No 48(64) 115(92) 6.47(2.91-14.40) <0.0001*
**CI- Confidence interval, * significant p-value.
32
3.3: Results of multiple logistic regression analysis
Table 3.9: Multivariate analysis
For the adjustment of possible interactions and confounding factors, multiple logistic
regression analysis was performed to arrive at the final model. Variables with p-value < 0.01
in bivariate analysis were considered for multiple logistic regression analysis.
Cases No %)
Controls No(%)
Unadjusted Odds Ratio(CI)
Adjusted OR(CI*)
P_value
Whether TB treatment interrupted
No1 48(64) 115(92) 6.47(2.91-14.39)
3.88(1.51-9.97)
<0.005
Age >452 59(79) 85(68) 1.73(0.89-3.38)
1.10(0.35-2.93)
0.982
Current smoke
No3 24(41) 44(65) 2.59( 1.26-5.34)
1.73(0.76-3.95) 0.192
Current consumption alcohol
No4 10(29) 17(45) 1.29( 0.61-2.76)
0.64(0.24-1.71) 0.368
1 yes reference
, 2 ≤ 45yrs reference
, 3 yes reference
, 4 yes reference
*CI-confidence interval. Other variables used- sex, ever smoke, ever alcohol.
The result concludes that the chance of failure is 3.88 times higher when there is
treatment interruption for tuberculosis.
33
CHAPTER 4
DISCUSSION
4.1 Socio economic and demographic factors influencing treatment outcome.
This study evaluates the non-cure in RNTCP patients in the state of Kerala.
In our study, we can see that more than 70% in both cases and controls were above 45years OR
1.74(CI 0.89-3.39). As per the (Ministry of H&FW,2012)TB India reports, more than 70 percent
of TB patients belong to the age group of 15-54yrs,this is also same in studies done in Kerala, the
majority of patients are above 50yrs of age (Balakrishnan et al, 2008). This may indicate that
new cases are not occurring among the younger population in Kerala, perhaps due to the success
of the BCG vaccination in the state. In a study done at a tertiary care setting in Malaysia
(Sulaiman, 2012) and another done at Harris County, Texas (Des Bordis, 2008) it was found that
tuberculosis without diabetes was more among old age group compared to tuberculosis with
diabetes among young age group.
The current study shows that females constitute 18% of the total, this is the same in many of the
studies done in Kerala, and according to WHO the male-female ratio is 1.6(Ministry of H&FW,
2012). The education, marital, and employment status does not show much difference between
the groups. The monthly income of 75 percent of treatment failure subjects is below 5000
Rupees; this can result in them neglecting medical care when there are untoward effects of drugs.
Studies suggests that on an average, 3 to 4 months of work time is lost as result of TB, resulting
in an average lost potential earning of 20-30 percent of the annual household income. This leads
to increased debt burden, particularly for the poor and marginalized sections of the population
(Ministry of H&FW, 2012).
In the current study the mean number of people staying together was found to be four and the
mean number of rooms at home was three. This study shows more treatment failure among the
34
subjects residing in the urban region of Trivandrum Corporation (Nemom and DTC tuberculosis
units).
4.2 Tobacco use
The tobacco history in the form of cigarette and beedi smoking, pan chewing etc. is notably
similar to a study done in Kerala where 72 percent adults used tobacco (Pradeepkumar AS,
2005). The current smoking status and daily smoking status are higher than the general
population(58 and 45percent among failures). According to GATS (Global Adult Tobacco
Survey) report the current smokers in India amount to 14 percent and the daily smokers to 10.7
percent. Evidently, smoking is an important risk factor for tuberculosis and can affect the
treatment outcome because smoking pattern is high among the tuberculosis subjects when
compared to the general population. The age of initiation of smoking in about, 60 percent are
below 18 years. This is again shown in one cross sectional study done in Kerala, where the mean
age of initiation of smoking among school boys was found to be 10.7years. The GATS report
shows that the average age of initiation as 17.8 among males and below 15years in 25.8 percent
female subjects. In the current study 81 percent of failure subjects and 78 percent of cured
subjects tried quitting tobacco use, the majority of whom were advised by a health worker during
the treatment period. The National report shows that 35.4 percent of the users seek advice from a
health care provider for quitting, which in turn shows that tuberculosis subjects take advantage of
the smoking cessation clinics that are being created to promote cessation of tobacco usage under
Ministry of Health and Family Welfare, Government of India (Thankappan KR, 2014).
In the current study second hand smoke (SHS) at home is found to be 15 percent among failure
subjects and 8 percent among cured subjects; this is below the National figure of 52.3 percent.
35
One systematic review (Jayadeep Patra et al, 2014), revealed that a relative risk (RR) of LTBI
associated with SHS exposure in children (pooled RR 1.64, 95% CI 1.00–2.83). Children showed
more than 3-fold increased risk of SHS-associated active TB (pooled RR 3.41, 95% CI 1.81–
6.45), which was higher than the risk in adults exposed to SHS (summary RR 1.32, 95% CI
1.04–1.68). Additionally, smokeless tobacco usage, which is almost comparable to the National
report of 25.9percent (WHO, 2010)
4.3 Alcohol consumption
The current data shows that 69 percent of treatment failure subjects and 51 percent of cured
subjects had history of ever consumption of alcohol which almost doubles the chance of noncure
OR 2.16 (CI 1.18-3.94), p-value0.013. The NSSO 2011-12 shows the average consumption
being 220ml/week, while that of Kerala being 196ml/week (10.2 liters/year) across all types of
alcohol. A trend from India is that the average age of initiation of alcohol use has reduced from
28 years during the 1980s to 17 years in 2007 (OECD report, 2015). The study of just under
2000 randomly selected 20-49 year old men from rural and urban areas in Northern Goa showed
that the proportion of men who started drinking in their teens rose from 20% for those born
between 1956 and 1960 to 74 percent for those born between1981-85 - a more than threefold rise
(Aravind Pillai, 2014)
4.4 Diabetes status
The current data shows that there is increased chance of noncure in diabetics OR 1.179 (95%CI
0.662-2.10) but it is not statistically significant. There is no significant difference between cases
and controls in prevalence of diabetes mellitus. According to (Stevenson CR, 2007; Jeon CY,
2008) as a result of systematic reviews of observational studies about diabetes among
36
tuberculosis subjects, the relative risk is found to be 3.1 (95% CI 2.3–4.3) with normal subjects.
The modelling suggests 20.8 percent of diabetes in sputum positive subjects (Ministry of
H&FW, 2012). The prevalence is almost similar to some of the studies done in Kerala about
prevalence of diabetes among tuberculosis subjects (Balakrishnan et al., 2008) (Nair et al., 2013)
and it is higher than the general population (Dooley KE, 2009), (Ruslami R, 2010). In Kerala the
prevalence of diabetes among the general population is 16-20 percent in urban areas and 9.1
percent in rural areas, the two studies were done at Trivandrum and Ernakulum, in Kerala (Kutty
VR, 1999), (Menon VU, 2006). One Indonesian study done at an urban tertiary care setting
among 634 subjects attending a TB clinic showed a prevalence of 15 percent, in Jakarta it is
found to be 17.1 percent and 11.6 percent in Bandung (Alisjahbhana et al., 2007). The current
prevalence of diabetes in Kerala is found to be 19.5 percent which is more than the rest of India
(Ramachandran, 2008).
The glycemic control was found to be poor among the subjects; as shown by the reported mean
PPBS (Post Prandial Blood Sugar). As several studies show poor glucose control among the
subjects with TB and diabetes (Riza et al, 2014); but here diabetes control is uniformly poor
among cured and non-cured. The table also shows the inadequate treatment these subjects are
following. The subjects following treatment with Insulin are found to be <15percent which
justifies the delay in adequate treatment iniation and maintenance among diabetics (Menon VU
et al., 2008). The duration of diabetes in 70 percent of failure subjects and 60 percent of cured
subjects below 5 years; this includes the diagnosis at the time of diagnosis of tuberculosis. This
figure is in contrast to one study done at Tamil Nadu in a tertiary care diabetes specialty hospital
setting where 36 percent subjects were with duration <5years and 13 percent 5-10years and 51
percent above 10yrs (Kumpatla et al., 2013). A cohort study evaluating TB treatment outcomes
37
as well as complications of diabetic patients infected with TB at 3 tertiary care settings in
Malaysia, the mean duration of diabetes was 4 years(Sulaiman et al., 2012).
4.5 Other diseases
About 24 percent of failures and 27 percent of cured subjects show other diseases including
coronary vascular disease, asthma, and hypertension, among which hypertension was the most
prevalent. Coronary vascular disease prevalence is different in different parts of India; with low
prevalence in the northern states (Chadha et al., 1987-88) and urban Delhi ICMR Taskforce
study in 1991-94 shows 11and 10 percent among men and women . Similarly, a studycarried out
in the rural areas of Kerala found 7.4 percent prevalence of CHD among the twenty-five plus age
group during 1990-91(Kutty VR, 1993) and Beegom Reported 13.9% of CHD prevalence in
1995 in the urban areas of Trivandrum, Kerala.
4.6 Tuberculosis related factors
The current study shows about 77 percent of subjects of both groups consulted a government
hospital for treating cough before diagnosis of tuberculosis, and 20 percent of the diagnosis is
done within one week of cough; but as per RNTCP guideline the TB suspect is defined as person
with history of cough of 2 weeks or more, but for these subjects, we could have missed this
20percent in early stage itself, if were followed the two weeks criteria. So this time we have to
rethink when will refer for diagnosis, and the rest took 1 week-1 month, and more than one
month duration of symptoms for diagnosis. It shows the delay in diagnosis. A study by WHO in
different countries showed a diagnostic delay of 44-124 days after the onset of symptoms (WHO,
delay in diagnosis, 2006). A study done in Melbourne, Victoria, Australia identified two cases of
tuberculosis (TB) in office coworkers. There with the use of restriction fragment length
polymorphism the Mycobacterium tuberculosis isolates were found to be identical. Contact
38
tracing was performed for 195 of 210 workers by means of the tuberculin skin test. Risk of
infection was assessed. Office contacts were exposed to infectious TB for 4 months; 24percent
of employees were infected. There was an association between sitting in proximity to the case
during the period of exposure (OR, 4.24; 95% CI, 1.06-19.67). Onsite workers had a higher risk
of being infected (OR 5.48; 95%CI1.51-23.54) than visiting workers. Workers in this office were
exposed to open pulmonary TB for prolonged periods. The prevalence of TB infection in that
study (24%) among these workers was high compared with the infection rate (2%-7%) in the
general community. Delay in diagnosis was the major factor responsible for the spread of TB in
this office (MacIntyre CR, 1995).
According to (John et al,2010) the disease cannot be controlled without shrinking the pool
of infected individuals by reducing the incidence of infection or reducing the progression of
latent infection to disease.
Almost all diagnosis of sputum positive cases was done at government hospitals because
the majority of accredited laboratories for sputum testing are at government hospitals. About
eight percent of subjects had a history of household contact of tuberculosis. So majority of the
infections are community acquired. The treatment centers are community centers and hospitals.
The hospitals acts as DOT centers in about 50 percent of cases and the distance between home
and the treatment center ranges from <500m to >1Km. So 50 percent of the subjects comes to
hospital for medicines, so this recommends infection control measures at hospitals. In one study
done at Mumbai about the determinants of poor adherence of anti-tuberculosis treatment it was
found that travel related cost factors were significantly associated with non-adherence in the
newly diagnosed patients (Suparna Bagchi, 2010). A similar result has been obtained from
studies done at South Asia and Malaysia (NaingNN, 2001).
39
The current study shows a significant number of noncured subjects interrupted treatment during
the course. From a study in Mumbai poor patient adherence to the treatment regimen is a major
cause of treatment failure and of the emergence of drug resistant TB (Suparna Bagchi, 2010).
But a study from Peru shows no relation between drug reactions and failure of treatment (Chavez
Pachas AM, 2004).
The predictors of failure determined in one of the studies in Uganda (Namukwaya E, 2011)
shows poor adherence to treatment and sputum positivity at two months of treatment. Drug
induced hepatitis is found to be associated with failure in some of the studies done at tertiary care
hospitals among newly diagnosed sputum positive cases (Baghaei P, 2010)
4.7 Result of bivariate analysis
The bivariate analysis with failure and cure as outcome variables and the variables with p value
less than 0.05 were taken for analysis to find out the association with the outcome. The factors
came to be significant were sex, age group, ever consumption of alcohol, current consumption of
alcohol, ever smoke, current smoke and history of tuberculosis treatment interruption.
The odds ratio for diabetes is 1.179 (95%CI, 0.66-2.10), p-value 0.578, so the chance of failure
of treatment in subjects with diabetes 1.18 times higher than subjects without diabetes though
statistically not significant; this means that diabetes does not seem to be a factor contributing to
tuberculosis treatment failure, but the prevalence of diabetes should be considered, however in
Tuberculosis patients.
40
4.1 Result of multivariate analysis
The main factor responsible for failure seems to be tuberculosis treatment interruption with
adjusted OR 3.88(CI 1.51-9.96). After adjustment for this factor, alcohol consumption and
tobacco failed to show up as risk factors for failure.
41
Chapter 5
Conclusion and Recommendations
The strongest factor responsible for failure of tuberculosis treatment is treatment interruption of
tuberculosis. The recognition of the determinants of failure is the important step that we have to
look into to prevent the chance of failure of treatment. All patients should be followed up
carefully after starting DOTS therapy. The cross reference of persons should be encouraged
between the TB and diabetic clinics for early detection of the disease. As per the evidences
shown we can see that a co-epidemic of tuberculosis and diabetes exists, so as we move towards
the elimination of tuberculosis addressing both issues are important.
5.1 Recommendations
As we can see from the Annual Report of RNTCP, the case finding efforts of Kerala is still low,
so as we move towards elimination of tuberculosis the booming of diabetes mellitus in Kerala
should not be ignored. Diabetes control is poor among the diabetics in the state this will add to
the early breakdown of disease in them. As per the WHO recommendations we should start
mechanisms for cross refferal of persons similar to AIDS Control Programme. It is
recommended to have a Registry of diabetics, which will make follow up of the persons easy.
Final recommendation is that whenever we start any kind of medicine to any type of patients the
system should be accountable for the completeness of the treatment, and correct follow up of the
patient, so that they also become responsible to the system.
42
5.2 Limitation of the study
It was planned to check the HbA1c of the diabetic study subjects for the actual diabetic control
status, but couldnot do that , so the actual diabetic control cannot be commented.
43
REFFERENCES
Aravind Pillai, Nayak MB, Greenfield TK, Bond JC, Hasin DS, Patel V (2014) Adolescent
drinking onset and its adult consequences among men: A population based study from India.
J Epidemiology Community Health 68(10): 922-927.
Arrossi S, HerreroMB, Greco A, Ramos S (2012) Predictive factors of nonadherence to
tuberculosis treatment in the metropolitan area of Beunos Aires, Argentina. Salud Colectiva
8(1): S65-S76
Alisjahbana B, Sahiratmadja E, Nelwan EJ, Purwa AM, Ahmad Y, Ottenhoff THM, et al.
(2007) The effect of type 2 diabetes mellitus on the presentation and treatment response of
pulmonary tuberculosis. .Clin Infect Dis: 45(4):428-35. Epub 2007 Jul 5.
Al-Delaimy WK, Willet WC, Maon JE, Speizer FE, Hu FB et al. (2001) Smoking and
mortality among women with type2 diabetes: The Nurses’ Health Study cohort. Diabetes
Care 12: 2043-2048
Baghaei P, Tabarsi P, Chitsaz E, Saleh M, Mariani M, Shemirani S, et al. (2010) Incidence,
clinical and epidemiological risk factors and outcome of drug induced hepatitis due to
antituberculous agents in new tuberculosis cases. Am j Ther 17(10): 17-22
Baghai P, Marjani M, Tabarsi P, Javanmard P,Masjedi MR (2013) Diabetes mellitus and
tuberculosis facts and controversies. Journal of Diabetes& Metabolic Disorders 12:58.
Balakrishnan S, Vijayan S, Nair S, Subramoniapillai J , Mrithyunjayan S, Wilson N, et al.
(2012) HighDiabetes Prevalence among Tuberculosis Cases in Kerala, India. PLoS ONE
7(10)
Baker MA, Harries AD, Jeon CY, Hart JE, Kapur A, Lonnroth K (2011). The impact of
diabetes on tuberculosis treatment outcomes: A systematic review. BMC Med 9: 81
Castle CS (2000) Clinical Relevance of Age-Related Immune Dysfunction. Clin Infect Dis
31:578-585
Chalasani N, Fontana RJ, Bonkovskv HL, Watkins PB, Davern D et al (2008) Causes,
clinical features, and outcomes from a prospective study of drug-induced liver injury in
United States. Gastroenterology 135(6): 1924-34.
Chavez Pachas AM, Blank R, Smith Fawzi MC, Bayona J, Batherra MC, Mithnic CD (2004)
Identifying early treatment failure on category I therapy for pulmonary tuberculosis in Lima
Ciudad, Peru. Int J Tuberc Lung Dis
8(1):52-58
Christopher Dye, Glaziou P, Floyd K, Raviglione M (2013) Prospects for Tuberculosis
Elimination. Annu. Rev. Public Health 34:271-286.
Creswell J, Raviglione M, Ottmani S (2011) Tuberculosis and noncommunicable diseases:
neglected links and missed opportunities. Eur Respir J 37(5):1269-1282
Danei G, Finucane MM, LuY, Singh GM,cowan MJ, Paciorek CJ, LinJK (2011) National,
Regional and global trends in fasting plasma glucose and diabetes prevalence since 1980:
44
systematic analysis of health examination surveys and epidemiological studies with 370
country-years and 2.7 million participants. Lancet 378: 31-40.
Delamaire M, Maugendre D, Moreno M, Le Goff, Allanic H, Genetet B (1997) Impaired
leucocytes functions in diabetic patients. Diabet Med 14(1):29-34
Dooley KE, Chaisson RE (2009) Tuberculosis and diabetes mellitus: convergence of two
epidemics. Lancet Infect Dis 9(12):737-746
Dirlikov E, Raviglione M, Scano F (2015) Global Tuberculosis Control: Toward the 2015
Targets and Beyond. Ann Intern Med 00: 1-8(accessed April2015)
Flynn, JM. (1935) The changing cause of death in diabetes mellitus. Am J Med Sci
189:157).
Feleke Y, Abdulkadir J, Aderaye G (1999) Prevalence and clinical features of tuberculosis in
Ethiopian diabetic patients. East Afr Med J 76(7):361-364
Harries AD, Lin Y, Satyanarayana S, Lonnroth k, Li L, Wilson N, et al. (2011) The looming
epidemic of diabetes associated tuberculosis: learning lessons from HIVassociated
tuberculosis. Int J Tuberc Lung Dis. 15(11):1436-44, i. doi: 10.5588/ijtld.11.0503. Epub
2011 Sep 6.
Harries AD, Kumar AMV, Satyanarayana S, Lin Y, Lonnroth K, Kapur A (2015) Diabetes
mellitus and tuberculosis: Programmatic management issues. Int J Tuberc Lung Dis 19(8):
879-886
Harries A D, Satyanarayana S, Kumar AMV (2013) Epidemiology and interaction of
diabetes mellitus and tuberculosis and challenges for care: a review. Public Health Action
3:S3-S9.
Hiwot Amare H, Gelaw A, Anagaw B, Gelaw B ( 2013) Smear positive pulmonary
tuberculosis among diabetic patients at the Dessie referral hospital, Northeast Ethiopia. Infect
Dis Poverty 2: 6.
Jabbar A, Hussain SE, Khan AA (2006) Clinical characteristics of pulmonary tuberculosis in
adult Pakistani patients with co-existing diabetes mellitus. East Mediterr Health J 12(5):
522-7.
Jeon CY, Murray MB (2008) Diabetes Mellitus Increases the Risk of Active Tuberculosis: A
Systematic Review of 13 Observational Studies. PLoS Med 5(7): e152.
Jayaram R, Gaonkar S, Kaur P, Suresh BL, Mahesh BN, Jayasree R, et al. (2003)
PharmacokineticsPharmacodynamics of Rifampin in an Aerosol Infection Model of
Tuberculosis. Antimicrob Agents Chemother 47(7): 2118–2124.
Joshi SR, Parikh RM (2007) India -diabetes capital of the world: now heading towards
hypertension: J Assoc Physicians India; 55:323-4
John TJ, Vipin M. Vashishtha, et al. (2010). Tuberculosis control must be scientifically
defined and soundly designed. Indian J Med Res 132:4-8
Kateruttanakul P, Unsematham S (2013) Drug resistance among new smear positive
45
pulmonary tuberculosis cases in Thailand. Int J Tuberc Lung Dis 17(6): 814-17.
Kaveeshwar SA, Cornwall J. (2014) The current state of diabetes mellitus in India. AMJ 7
(1): 45-48. http//dx.doi.org/10.4066/AMJ.2013.1979
Kirenga BJ, Ssengooba W, Muwonge C, Nakiyingi L, Kyaligonsa S, et al. (2015)
Tuberculosis risk factors among tuberculosis patients in Kampala Uganda: Implications of
tuberculosis control. BMC Public Health 15: 13 doi: 10.1186/s1288901513763
Kapur A Harries AD. (2013) The double burden of diabetes and tuberculosis: public health
implications. Diabetes Res Clin Pract.
Kutty VR, Soman CR, Joseph A, Pisharody R, Vijayakumar K (2000) Type 2 diabetes in
southern Kerala: variation in prevalence among geographic divisions within a region. Natl
Med J India 13: 287-292.
Lonroth,R,Corbett E, Golub J, Godfrey-Fausette P,Uplekar M, Raviglione M.(2013 )
Systematic screening for active tuberculosis: rationale, definitions and key considerations. Int
J Tuberc Lung Dis 17(3):289-98. doi: 10.5588/ijtld.12.0797
Lienhardt C, Fielding K, Sillah JS, Bah B, Gustafson P, Wandorff D et al. (2005)
Investigation of the risk factors for tuberculosis: a case control study in three countries in
West Africa. Int J Epidemiol 34(4):914-23.
Lienhardt C, Glaziou P, Uplekar M,et al. (2012) Global tuberculosis control: lessons learnt
and future prospects. Nat Rev Microbiol. 10:407-16. [PMID: 22580364 doi:
10.1038/nrmicro2797
Lonnroth K, Roglic G, Harris AD (2014) Improving tuberculosis prevention and care through
addressing the global diabetes epidemic: from evidence to policy and practice. Lancet
Diabetes Endocrinol 2:730-39.
MacIntyre CR, Plant AJ, Hulls J, et al. (1995) High rate of transmission of tuberculosis in an
office: impact of delayed diagnosis. Clin Infect Dis 21(5):1170-1174.
Muniyandi M, Rao VG, Bhat J , Yadav R (2015) Performance of Revised National
Tuberculosis Control Programme (RNTCP) in tribal areas in India. Indian J Med Res 141:
624-629.
Martens GW, Arikan MC, Lee J, Streeton JA, Graham NM, Rouch GJ (2007) Tuberculosis
Susceptibility of Diabetic Mice .Am J Respir Cell Mol Biol 37(5): 518–524
Mohan V, Shah S, Saboo B (2013) Current glycemic status and diabetes related
complications among type 2 diabetes patients in India: data from the A1cheive study. J Assoc
Physicians India 61(1): 12-15
Naing NN, D'Este C, Isa AR, Salleh R (2001) Factors contributing to poor compliance with
antiTB treatment among tuberculosis patients. Southeast Asian J Trop Med Public Health
32(2):369-82
46
Namukwaya E, Nakwagala FN, Mulekya F, Mayanka-Kizza H, Mugerva R (2011) Predictors
of treatment failure among pulmonary tuberculosis patients in Mulago hospital, Uganda. Afr
Health Sci 11(1): S105–S111.
Nijland HM, Ruslami R, Stalenhoef JE (2006) Exposure to rifampicin is strongly reduced in
patients with tuberculosis and type 2 diabetes.Clin Infect Dis 43:848–54
Nair S, Kumary AK, Subramanian Pillai J (2013) High Proportion of Undiagnosed diabetes
among tuberculosis patients in peripheral health facilities in Kerala.Public Health Action
3(S): S38-S42
Patra J, Jha P, Rehm J, Suraweera W (2014) Tobacco Smoking, Alcohol Drinking, Diabetes,
Low Body Mass Index and the Risk of Self-Reported Symptoms of Active Tuberculosis:
Individual Participant Data (IPD) Meta-Analyses of 72,684 Individuals in 14 High
Tuberculosis Burden Countries. PLoS ONE 9(5): e96433. doi:10.1371/journal.pone.0096433
Patra J, Bhatia M, Suraweera W, Morris SK, Patra C,Gupta C, Jha P (2015) Exposure to
Second Hand Smoke and the Risk of Tuberculosis in Children and Adults: A Systematic
Review and Meta Analysis of 18 Observational Studies. PLoS Med 12(6): e1001835.
Pradeepkumar AS, Mohan S, Gopalakrishnan P, et al. (2005) Tobacco use in Kerala: findings
from three recent studies. Natl Med J India 18(3):148-53.
Pablos-Méndez A, Blustein J, C A Knirsch CA (1997) The role of diabetes mellitus in the
higher prevalence of tuberculosis among Hispanics. Am J Public Health 87(4): 574–57
Ponce-De-Leon, A., Garcia-Garcia Md Mde, L., Garcia-Sancho (2004) Tuberculosis and
diabetes in southern Mexico, Diabetes Care. ; 27(7):1584-90
Peloquin CA (2002) Therapeutic drug monitoring in the treatment of tuberculosis. Drugs,
62:2169–83
Raviglione M, Krech R (2011) Tuberculosis: still a social disease [Editorial]. Int J Tuberc
Lung Dis.; 15(2):S6-8. [PMID: 21740652] doi:10.5588/ijtld.11.0158
Ruslami R, Nijland HMJ, I. Gusti N. Adhiarta, Kariadi HKS, Alisjahbana B, et al. (2010)
Pharmacokinetics of Antituberculosis Drugs in Pulmonary Tuberculosis Patients with Type 2
Diabetes. Antimicrob Agents Chemother 54(3): 1068–1074.
Ramachandran A, Snehalatha C (2009) Current scenario of diabetes in India. Journal of
Diabetes 1:18-28
Rathod HK, Darade SS, Chitnis UB, et al. (2014) Rural prevalence of type 2 diabetes
mellitus: A cross sectional study. J Soc Health Diabetes 2:82-6
Rayfield JE, Audit JM, Keusch TG, et al. (1982) Infection and diabetes: The case of glucose
control. Am J Med 72(3): 439-450
Reid MJA,McFadden N, Tsima BM (2013) Clinical challenges in the co-management of
diabetes mellitus and tuberculosis in southern Africa. JEMDSA 18(3):135-140
47
Satyanarayana S, Nair SA, Chadha SS, Shivashankar R, Sharma G (2011) From Where Are
Tuberculosis Patients Accessing Treatment in India? Results from a Cross-Sectional
Community Based Survey of 30 Districts. PLoS ONE, 6(9): e24160. doi:
10.1371/journal.pone.002416
Subrmanya Rao MS, Unnikrishnan KP (2004) A cohort analysis of performance of Revised
National Tuberculosis Control Programme in Kerala. NTI Bulletin 40(3&4): 70 – 74.
Sumitra Debroy (2014).Diabetes-TB May Be Most Dreaded Combo. The Times Group e-
paper
Suparna Bagchi, Guirish Ambe, Nalini Satyakumar (2010) Determinants of Poor Adherence
to Anti-Tuberculosis Treatment in Mumbai, India. Int J Prev Med 1(4): 223-232.
Sulaiman SSA, Khan AH, Muttalif AR, Hassali MA, Ahmad N, Iqbal MS (2013) Impact of
Diabetes Mellitus on Treatment Outcomes of Tuberculosis Patients in Tertiary Care Setup.
Am J Med Sci 345(4):321–325.
Swai AB, McLarty DG, Mugusi F (1990) Tuberculosis in diabetic patients in Tanzania Trop
Doct 20(4):147-150
Thankappan KR, Mini GK (2008) Case-control study of smoking and death in India. The
New England Journal of Medicine 358: 2842–2843
Thankappan KR (2014) Tobacco cessation in India: A priority health intervention. Indian J
Med Res. 139(4): 484–486.
Young F, Critchley JA, JohnstoneKL, Unwin NC (2009) A review of comorbidity between
infectious and chronic disease in Sub Saharan Africa: TB and Diabetes Mellitus, HIV and
Metabolic syndrome, and the impact of globalization. Global Health 5:9
Wild S, Roglic G, Green A, Sicree R, KingH (2004) Global prevalence of diabetes: estimates
for the year 2000 and projections for 2030. Diabetes care 27(5): 1047-53
Will JC, Galuska DA, Ford ES, Mokdad A, Calle EE (2001). Cigarette smoking and diabetes
mellitus evidence of a positive association from a large prospective cohort study. Int J
Epidemiol. 30: 540-6
Warrell DA, Cox TM, Firth JD. (2010). The Oxford Textbook of Medicine. (5th ed). Oxford
University Press
World Health Organization/International Union Against Tuberculosis and Lung Disease.
Collaborative framework for care and control of tuberculosis and diabetes. Geneva,
Switzerland: WHO; 2011.
.Ministry of Health and Family Welfare int Government of India. Fact sheet (2010) Global
Adult Tobacco Survey .Available at: www.who. /tobacco/surveillance/survey/gats/en
en_tfi_india_gats_fact_sheet (1).pdf.
48
Ministry of Health & Family Welfare, Government of India (2011) National Cardiovascular
Disease Database.
http://www.searo.who.int/india/topics/cardiovascular_diseases/NCD_Resources_National_C
VD_database-Final_Report.pdf?ua=1
Ministry of Health & Family Welfare Government of India (2012) Revised National TB
Control Programme Annual Status Report. TBIndia Available from
www.tbcindia.nic.in/pdfs/TB%20India%202012-%20Annual%20Report.pdf.
Ministry of Health & Family Welfare Government of India (2013) Revised National TB
Control Programme Annual Status Report. TBIndia Available from
www.tbcindia.nic.in/pdfs/tb%20india%202013.pdf
.World Health Organization(WHO) The Global TB Plan to Stop TB 2011-2015-Stop TB
Partnership. www.stoptb.org/assets/documents/.../tb_globalplantostoptb2011-2015.pdf.
World Health Organisation (WHO) Definitions and reporting framework for tuberculosis
– 2013 revision (updated December 2014)
http://www.who.int/iris/bitstream/10665/79199/1/9789241505345_eng.pdf.
World Health Organization (WHO) (2006) Diagnostic and treatment delay in tuberculosis:
An in-depth analysis of the health-seekingbehaviour of patients and health system response
in seven countries of the Eastern Mediterranean Region.
http://www.emro.who.int/dsaf/dsa710.pdf.
. World Health Organization (2014). WHO/ Global Tuberculosis Report. Available from
http://www.who.int/tb/publications/global_report/en/ (Accessed on 15 Feb 2015).
World Health Organization WHO (2014) Global status report on noncommunicable diseases
www.who.int/entity/nmh/publications/ncd-status-report-2014/en/ - 28k(accessed on June
2014)
CSDH (2008). Closing the gap in a generation: health equity through action on the social
determinants of health. Final Report of the Commission on Social Determinants of Health.
Geneva, World Health Organization. Available from
www.who.int/social_determinants/final.../csdh_finalreport_2008.pdf.
International Diabetes Federation (2014) IDF Diabetes Atlas, Sixth Edition. Brussels:
International Diabetes Federation; 2013. Available from:
http://www.idf.org/diabetesatlas/download-book .Accessed March 20, 2014
UNESCO [online] (2014) LAMP-Literacy Assessment And Monitoring Programme.
Available from http://www.uis.unesco.org/Literacy/Pages/lamp-literacy-assessment(accessed
on 2/2015)
The Indian Express (May 2015) Alcohol consumption rising fast in India: OECD report
49
http://indianexpress.com/article/india/indiaothers/
alcoholconsumptionrisingfastinindiaoecdreport
World Health Organisation (2008) Implementing the Stop TB Strategy: A hand book for
national tuberculosis control programmes. Geneva (WHO/HTM/TB/2008.401)(Accessed
on September 2015)
.
List of Abbreviations
TB Tuberculosis
LTBI Latent Tuberculosis Infection
WHO World Health Organisation
HIV Human Immunodefficiency Virus
RNTCP Revised National Tuberculosis Control Programme
DOTS Directly Observed Treatment Shortcourse
CI Confidence Interval
MDR Multi Drug Resistant Tuberculosis
LMICs Low and Middle Income Countries
DM Diabetes Mellitus
PTB Pulmonary Tuberculosis
DALY Disability Adjusted Life Years
HBCs High Burden Countries
NTP National Tuberculosis Control Programme
SDH Social Determinants of Health
ILO International Labor Organisation
ASH Action on Smoking and Health
TU Tuberculosis Unit
MDG Millennium Development Goal
NSSO National Sample Survey of India
PTB Pulmonary Tuberculosis
TBC India Tuberculosis Council of India
Sree Chitra Tirunal Institute of Medical Science and Technology -
Trivandrum
“Association of treatment outcome in RNTCP patients in Trivandrum District with diabetes status -a case control study “
Interview schedule 1 Subject code
TB No.
Socio demographic profile
2 Name S1 3 How old were you on your last birthday? S2 4 Sex
Male : 1,
Female : 2
S3
5 What is the highest level of education you
have completed?
(1) No formal
schooling (2) Elementary
school completed (3) High school
completed
(4) Higher
secondary school
(5)
University/college completed
(6) Post
graduate degree
S4
ANNEXURE 1
(7) Others
(specify)......................
6 Marital status Married :1,
Never married :2,
divorced separated :
3;
widowed :4,
S5
7 What is your current occupation? Government
employee:1, Unemployed:2,
Private: 3
Self
employed/business:4,
Home maker:5,
Pensioner:6,
Manual labor:7
S6
8 What is your total household monthly
income?
<5000:1,
5000-10,000:2,
>10,000:3
S7
9 What is the type of your Rationcard? S8 10 The type of house
Kutcha:1,
semipucca:2,
pucca:3
S9
11 Religion Hindu:1,
Christian:2,
S10
Muslim:3,
Others(specify)
12 How many persons are staying with you in
your house ?
S11
13 The number of rooms in your house?
S12
Tobacco use 14 Have you ever smoked
[1] yes
[2] No
T1
15 Do you currently smoke any tobacco
products such as
cigarettes/beedi/others?
Yes:1,
No:2
The answer to
qn T2 IS no ,
skip to T7
T2
16 Do you currently smoke tobacco products
daily?
Yes :1
No :2
T3
17 How old were you when you first started
smoking daily?
Age in years
[77] Don't
know
T4
18 How many of the following do you smoke
each day?
[1] Cigarette/day
[2] beedi/day
[3] others/day
T6
19 Did you stop smoking? [1] yes
[2]No
IF NO, SKIP TO
T11
T7
20 how many cigarettes/beedis were you
using per day before quitting?
T8
21 What was the reason to quit smoking? T9 22 How long did you smoke? (in years)
T10
23 During past one week how many days did
someone in your home smoke in your
presence?
No. of days
[77] Don't know
T11
24 Do you currently use any smokeless
tobacco products? [1] Yes
[2] No
IF NO, SKIP TO
A1
T12
25 Do you currently use any smokeless
products such as (snuff, chewing tobacco,
betel daily)
[1] yes
[2] No
T13
26 How old were you when you first started
using smokeless tobacco daily? Age in years
[77] Don't know
T14
27 How many of the smokeless tobacco
products do you use daily on an average? [1] pan Masala-
Packet/day
[2] Paan/day
[3] Gutka packet/day
[4] Snuff
times/day
[5] Betel with
tobacco/day
[6]
T15
Others(specify).........
Alcohol consumption
2
8
Have you ever consumed alcoholic drink
such as beer, wine, whisky, locally
prepared alcohol?
Yes:1
No;2
IF NO, SKIP TO
M1
A1
29 Have you ever consumed an alcoholic drink
such as beer, wine, whisky, locally
prepared alcohol in the past 12 months?
[1] Yes
[2] No
A2
30 If yes, how frequently have you consumed
at least one drink of alcohol in the past 12
months?
[1] 1-3 days/month
[2] 1-4 days/week
[3] 5-6 days/week
[4] Daily
A3
31 How many years have you been taking
alcohol in whole(years) Years A4
32 Have you consumed alcohol in the past 30
days? [1] Yes
[2] No
A5
33 During the past 30 days when you drank
alcohol, on an average how many standard
alcoholic drinks did you have during one
occasion?
Number
[77] Don't know
A6
34 During each of the past 7 days, how many
standard alcoholic drinks did you have
each day?
(standard drink: One standard glass of
beer, wine or any form of spirit. 1 Std glass-
8-13 grams of alcohol)
[1] Monday
[2] Tuesday
[3] Wednesday
[4] Thursday
[5] Friday
[6] Saturday
[7] Sunday
A7
Physical Measurements
35 Weight in Kgs
M1
36 Height in cms
M2
37 BMI
M3
History of raised blood pressure
38 Have you ever had your blood pressure
measured by a doctor or other health
worker
[1] yes
[2] No
H1
39
Blood pressure SBP(systolic blood
H2
pressure) :
DBP(diastolic blood
pressure) :
40 Have you ever been told by a doctor/
health worker that you had
hypertension(pressure)
[1] yes
[2] No
H3
Diabetes
41 Random blood sugar(mg/dl)
D1
Date
42 Have you ever been diagnosed with
diabetes? Yes :1,
No :2
IF NO SKIP TO
O1
D2
43 If yes, for how many years have you been
suffering from it? D3
44
Fasting blood sugar(mg/dl) D4
Date
45 Postprandial blood sugar(mg/dl)
D5
Date
46 HbA1c(%)
D6
Date
47 S.Creatinine(micromol/L) with date-
D7
Date
Diabetic treatment
48 Are you on regular follow up for diabetic
treatment (at least once in a month)? Yes :1
No :2
D8
49 From where are you taking treatment for
diabetes? Public facility :1,
Private facility :2
D9
50 Currently are you on medication for
diabetes? Yes :1,
No :2
D10
51 Insulin Yes :1,
No :2
D11
52 If, yes, frequency
D12
53 Dosage
D13
54 Tablet Yes :1,
D14
No :2
55 If yes, Name of medicines
D15
56 Frequency
D16
57 Dosage D17
58 Are you on some other systems mode of
treatment for diabetes ? Yes :1,
No :2
D18
59 Name of the type of medication D19
60 Frequency D20
61 Did you missed the diabetes treatment
during TB treatment? [1]Yes
[2] No
D21
62 What is the reason? D22
63 Does anyone in your family have a history
of diabetes? Yes :1,
No :2
D23
64 How you are related with him/her? D24
History of other diseases 65 Are you on medication for any other
diseases Yes :1,
No :2
O1
66 hypertension Yes :1,
No :2
O2
67 CVD Yes :1,
No:2
O3
68 hypothyroidsm Yes :1,
No:2
O4
69 COPD/Asthma? Yes :1,
No :2
O5
70 Are you suffering from other diseases,
please specify ….......................................
O6
71 Did you test for HIV during TB treatment?
If yes, the result................... Positive :1,
Negative :2,
Unknown :3
O7
Tuberculosis 72 Where did you go when you had cough in
the beginning? Govt hospital :1,
Private physician:2,
private hospital :3,
Medical store:4,
self treatment :5,
alternate medicine :6
TB1
73 From where were you diagnosed to have
tuberculosis ? Govt :1,
Others :2
TB2
74 When did you start treatment for TB3
tuberculosis?
75 For how long did you take other
medications for cough before being
diagnosed for tuberculosis? >1month :1,
1 week to 1 month :2,
<1 week :3
TB4
76 Does any one in your home have a history
of tuberculosis? Yes :1,
No :2
TB5
77 If yes, how many months/years back? TB6 78 Have they been treated ?
Yes :1,
No:2
TB7
79 How are you related to the person? Spouse :1,
mother/father :2,
sibling:3,
Others :4
TB8
80 Whether your sputum have been taken for
culture and sensitivity? Yes :1,
No :2
TB9
81 The result of culture and sensitivity? Positive :1,
Negative :2
TB10
82 When did the medicine for tuberculosis
end?
TB11
83 From where did you take medicine for
tuberculosis? Hospital :1,
Anganwadi :2,
Asha :3,
other community
volunteer ;4, self :5
TB12
84 What is the approximate distance between . TB13
your home and DOT CENTRE?
….......................
85 Do you have any history of missed/
stopped medication during TB treatment? Yes :1,
No :2
S TB14
86 If yes, what is the reason? Drug allergy :1,
Drug Intolerance :2
Difficulty in reaching
DOT CENTRE :3
Non availability of
medicine : 4
Fasting :5
Others :6
TB15
Diet 87 Are you vegetarian/non-vegetarian?
[1] yes
[2]No
Dt1
88 Did you do any dietary modification during
treatment for tuberculosis? Yes :1,
No :2
Dt2
89 If yes, the important change you made in
the diet?
Dt3
Annexure 2
Structured interview schedule- Malayalam
ANNEXURE 3
Research Information sheet and consent form-
English and Malayalam
1
INFORMED CONSENT
“Association of treatment outcome in RNTCP patients in Trivandrum district with
diabetes status- A case control study”
Information sheet
Good morning/afternoon/evening,
I am Dr. Shabna, currently doing Master of Public Health(MPH) at SCTIMST(Sree
Chitra Tirunal Institute of Medical Sciences and Technology). I am conducting a study,
“Association of treatment outcome in RNTCP patients in Trivandrum district with
diabetes status- A case control study”, as part of the requirement of the course.
Purpose of study
The aim of the research is to study the association between non-cure of tuberculosis in
patients treated under RNTCP program and prevalence and control of diabetes among
them, and other risk factors associated with noncure.
For this study Trivandrum district has been selected and the subjects will be interviewed
as per your willingness for participation. The subjects who were sputum positive at the
beginning of the treatment and those who have completed their treatment during the study
period are selected for the study. The non-cured patients will be taken as cases and cured
are taken as controls. If the study subjects are diabetic their sugar status and other
parameters will be recorded and blood sugar control status will be tested using HbA1c.
The cost of the test will not be collected from you. You have to spend a total of 20
minutes for an interview and answer a prepared set of questions I will be recording the
interview. If you participate in the study by answering the interview schedule, I will be
greatful to you for providing the information.
Benefits from participation
There will not be any direct benefit for you if you participate in the study, but your
participation will help in generating knowledge about TB.
Discomfort/harm from participation
Participation in the study will not impose any risk to health. Some questions related to
your health, behaviour and personal history as well as measurements may cause little bit
discomfort.
Confidentiality
ANNEXURE 3
2
The information provided by you will be kept confidential and will be used for research
purpose only. Your personal identity will not be revealed to anyone. All copies of the
filled interview schedules and consent forms will be kept under custody of the principal
investigator and will be destroyed when they are deemed no longer needed.
Voluntariness.
Your participation is voluntary and you are free to quit this interview at any point of time.
If you have any doubt regarding the study please feel free to contact me.
Dr Shabna.D.S Dr Mala Ramanathan
MPH 2014 Hon secretary IEC
SCTIMST SCTIMST
[email protected] [email protected]
My contact No.9446309282 0471-2524234
3
Consent statement to take part in the study
I ….........................................................................................aged..............................
Declare that..........
[1] I Have read and understood the information in consent form
[2] The nature of the study and my involvement has been explained
[3] All my questions have been answered .
[4] By signing this consent form, I understand what will be expected from me
[5] I understand that the information will be used only for the study purpose
[6] I am aware that I can withdraw at any time.
Yes, I am agreeing to the interview
Signature/Left thumb impression …..........................
If respondent only giving verbal consent and not willing to sign or thumb impression
Signature of the witness...................................................................................................
Name and address & relation of the
witness.........................................................................................
No, I am not participating in the interview.
