European Journal of Cardiovascular Medicine

The World Health Organization (WHO) has estimated that, unless tuberculosis control is strengthened, one billion people will be infected with TB bacillus, 200 million people will develop clinical tuberculosis and 35 million will die from it over next 20 years. Although the incidence of TB has declined greatly during the twentieth century in the industrially developed nations, these nations are now experiencing an upsurge of this disease. Multi-drug resistant tuberculosis (MDR-TB) has become a major problem in several regions throughout the world and in some countries extensively resistant forms of the disease (XDR-TB) have emerged and have raised a serious threat of untreatable disease. The WHO became so concerned about the relentless spread of TB throughout the world that it declared this disease as a ‘Global Emergency’ in 1993. Tuberculosis caused by strains resistant to rifampicin and isoniazide, irrespective of other resistances, is termed multi-drug resistant tuberculosis (MDR-TB) and such patients do not respond to the standard short-course therapeutic  regimens and are must be treated for extended periods with regimens that are costly and more likely to cause adverse effects. As a consequence, there is a high risk that patients will go untreated in resource-poor regions and pass the infection to others. Defaulting on treatment will lead to development of resistance to first line of anti-tubercular drugs and such repeated defaulters will end up as MDR-TB/XDR-TB patients, which according to WHO are a serious threat of untreatable disease¹.

The TB mortality rate has decreased more than 40% since 1990 and the South-East Asia Region is on track to achieve the global target of a 50% reduction by 2015. A decline in prevalence rate is observed in all member states and in some countries it has reached over 50% reduction from 1990 levels².

Though India is the second-most populous country in the world, one fourth of the global incident TB cases occur in India annually. India’s TB control program is on track as far as reduction in disease burden is concerned. There is 42% reduction in TB mortality rate by 2012 as compared to 1990 level. Similarly there is 51% reduction in TB prevalence rate by 2012 as compared to 1990 level³.Tuberculosis prevalence per lakh population has reduced from 465 in year 1990 to 230 in 2012. In absolute numbers, prevalence has reduced from 40 lakhs to 28 lakhs annually³. Besides the disease burden, TB causes an enormous economic burden to India. In India TB is mainly a disease of the poor and most of the victims are, migrant laborers, slum dwellers, residents of backward and overcrowded areas and people residing in tribal pockets. Poor conditions, malnutrition and shanty housing are the main reasons for spread of TB⁴. A patient of TB takes an average of 3 to 4 months to recuperate, leading to loss of income which in turn is disastrous for those struggling against poverty and such people are likely to be defaulters⁵. Karnataka is the state in South India with 628 lakh population and 44714 smear positive patients in the year 2013⁶.As per 2013, Karnataka has 141 TB Units and 665 Designated microscopic centers (DMC) and has a default rate of 17 %³. Dakshina Kannada (DK) District of Karnataka with a total population of 2,089,649 is located in the southern most part of the state and has an annual case notification rate of 78⁶. DK District covers 4859 sq.kms in area and has a total 344 Directly Observed Treatment short-course (DOTS) centers and 5 Treatment Units (TU). The district has an almost equal male to female ratio (1034714:1054935)⁶.

Hence these factors trigger the need to undertake this study to understand the risk factors that are associated with default and to suggest appropriate health interventions to reduce default which would in turn decrease the treatment duration and decrease the burden of social, financial and psychosocial burden on the family.

The study was conducted in DK District of Karnataka. The DK district has 5 TUs namely Mangalore, Moodbidri, Puttur, Belthangady and Bantwal which are located at a distance of 16 km, 41 km, 46 km, 64 km and 29 km respectively from the Medical College in Deralakatte. Mangalore TU comes under the urban area and the rest four TUs fall under the rural category. The total numbers of patients registered under DOTS in the year 2014 are 1642

Study participants include all TB patients registered under five TU units from January 1^st 2014 to December 31^st 2014.

Cases were defined as TB patients who received anti-tuberculosis treatment for one month or more from any source and returns to treatment after having defaulted, i.e., not taken anti-TB drugs consecutively for two months or more, and is found to be sputum smear positive and registered under DOTS during 1^st Jan 2014 to 31^st Dec 2014 as Treatment after Default (TAD).

Controls  are defined as new TB cases registered under DOTS during the same period, who had not defaulted and completed TB regimen as per RNTCP guidelines.Controls were matched to cases by age and gender at a ratio of cases to controls is 1:2.

Inclusion criteria:

Subjects aged 18 years and above and who consent to participate in the study and registered under DOTS.

Exclusion criteria:

1. a) The TB patients who are transferred out and could not be contacted even with two visits.
2. b) Non-availability of health records of patients.

Sample size and sampling method

Final sample consisted of 68 cases and 136 age and gender match controls were enrolled by purposive sampling. A pre-designed, pre-tested semi structured questionnaire was formulated based on review of literature of similar studies. The questionnaire was further reviewed by the subject experts from Community Medicine department for content validity. Sources of data included TB registers and Interview.

Statistical Analysis: Data was analyzed with SPSS version16. Chi- square (Χ²) test was applied to study the association of various study variables with cases and controls. Those factors found significant on univariate analysis (p<0.05) were subjected to logistic regression analysis to look for odds of defaulting with respect to the risk factor.

The mean age of the study population was 42.9±13 years. Majority  were males (91.2%) and females were 8.8%.

Table 1: Distribution of Cases and Controls according to Tuberculosis Units (TU’s) in Dakshina Kannada District.

Table 2: Age group and Gender wise distribution of study subjects. (n=204)

Table3: Distribution of subjects according to socio demographic profile. (n=204)

Majority of the study participants belonged to Hindu religion (76%), married (61.3%), literate (52.5%), belonging to Joint family (56.4%), employed (83.3%), belonged to a family of ≤ 5 members (57.8%), resided in the same residence for > 24 months (82.8%) and the study subjects were equally distributed across rural and urban regions (50%). Majority of the study participants belonged to upper lower class (36.8%) and upper middle class (37.3%) class of socio economic status according to Modified BG Prasad 2013 classification There is no statistical difference between cases and controls with respect to age and gender (p=>0.05).

Proportion of Hindus (85.3%) were found to be high among cases when compared to controls (71.3%) and this difference was found to be statistically significant (p <0.05). It was observed that higher proportion of patients who were single discontinued on DOTs treatment (67.6%) as compared to controls (24.3%) and was found to be statistically significant with p value <0.05. Proportion of illiterates with respect to cases (70.6%) was found to be high when compared to controls (43.4%) and was found to be statistically significant (p <0.05). It was observed that higher proportion of patients who discontinued on treatment were those who were working for >8 hours (80.9%) as compared to controls (36.0%) and was found to be statistically significant  (p <0.05). Higher proportion of cases ie41.2% compared to controls ie10.3% had family history of TB and this difference was found to be statistically significant (P <0.05). Proportion of patients who had stayed for <24 months in treatment area with respect to cases (36.8%) was found to be high when compared to controls (7.4%) with p value <0.05.

Table 4: Association of Provider related factors with cases and controls (n=204)

(*p<0.05 statistically significant)

Majority of the controls (83.1%) reported that, disease has been explained by DOTS provider as compared to cases (60.3%) which was found to be statistically significant (p <0.05). significantly good number of cases (16.2%) reported that DOTS provider did not insist on swallowing tablets in front of them than controls (4.4%) with p value <0.05.There was a statistically significant association between cases (45.6%) and controls (11.8%) with respect to attitude /behavior of the provider (p <0.05). Majority of cases (54.4%) was high compared to controls (32.4%) with respect to collection of medication by family members and was found to be statistically significant (p <0.05). There was a statistically significant association between cases (23.5%) and controls (8.1%) with respect to distance of treatment centre (p <0.05).

Table 5: Logistic regression analysis of Provider related risk factors with study subjects (n=204)

(*p<0.05 statistically significant, (r) is reference)

Subjects to whom the disease was not explained by DOTS provider had 3.23 time odd of defaulting, when compared to whom it was explained (p <0.05). There is 4.18 times odds of default among subjects who were not insisted to swallow medication in front of the provider compared to those who were insisted (p <0.05). Subjects who felt that the attitude and behavior of the provider to be unsatisfactory, compared to those who felt it satisfactory, had 6.284 times odds of defaulting on treatment (p <0.05).Subjects whose family was allowed to collect medication in absence of the subject had 2.496 times odds of defaulting on treatment compared to those who were not allowed to collect(p <0.05). Subjects who had to travel a distance of  > 5 km’s, in comparison to those who had to travel < 5 km’s, had 3.49 times odd of defaulting on treatment (p <0.05).

Table 6: Multivariate logistic between provider related risk factors with DOTS defaulters (n=204) [R²=46.1%]

(*p<0.05 statistically significant, (r) is reference)

On applying multivariate logistic regression, the provider related factors namely attitude and behavior of provider, collection of medicines by family members, distance from treatment centre and explanation of disease by provider were found to be the independent risk factors for defaulting on DOTS.

In the present study, among the study participants interviewed (204), majority (60.3%) of the study participants belong to economically productive age group (<30-49 years), with a mean age of 42.9±13 years. A similar study conducted by Mishra.P et al⁷ showed that the mean age of cases was 42.9±18.2 years and controls were 38.7±16.3 years. A cross sectional study by N.Pandit et al⁸ in Anand district, Gujarat stated that majority (85%) of the study population belonged to economically productive age group. As tuberculosis affects economically productive age group, it causes substantial social and economic disruption of the affected family.

The association of age and gender with default, in which both cases and controls were similar with respect to age and gender as the difference between both was statistically not significant (p>0.05). Our study cases and controls were matched with age and gender. A similar case control study by Vijay.S, Kumar.P et al depicts similar findings.⁹

In our study population, majority (91.2%) of cases were males. Study conducted in similar setting by Vijay.S et al³⁵ showed majority of (CAT I 89.6% &CAT II 90.9%) of cases to be males.

In the present study, disease explained by the DOTS provider was significantly associated with cases (39.7%) and controls (16.9%) and this difference was found to be statistically significant (p <0.05). similar findings were found in studies: Our study also found that, subjects to whom the disease was not explained by the DOTS provider had 3.23 time odds of defaulting, when compared to whom it was explained (p <0.05).In a study by Slama K et al¹⁰ reported that, cases were more likely than controls to report that they had not received enough education about TB at the beginning of treatment.

In the present study, there was a statistically significant association between cases (16.2%) and control (4.4%) with respect to swallowing medication in front of the provider (p <0.05) and there was 4.18 times odds of default among subjects who were not insisted by DOTS provider to swallow medication in front of them as compared to those who were insisted (p <0.05).A case control study by Finlay A et al¹¹, found half of the cases and controls reported taking treatment without direct supervision.

In the present study, most of the cases (45.6%) felt the attitude/behavior of the DOTS provider is not satisfactory as compared to controls (11.8%) with (p <0.05) and also subjects who felt that the attitude and behavior of the provider to be unsatisfactory, compared to those who felt it satisfactory, had 6.9 times odds of defaulting on treatment (p <0.05).A case control study by Finlay A et al¹¹ states that defaulters experienced unsatisfactory behavior of the provider than non-defaulters. Study by Satti.SBR et al⁶⁶ also found higher proportion of DOTS defaulters (65.83%) were not satisfied with conduct of health personnel in DOTS centers as compared to controls (18.33%) and conduct of health personnel were significantly and strongly associated (OR=8.5) with default. Poor communication skills of the health workers, rude and unhelpful behavior reported as reasons for default by subjects¹².

In the present study the odds of defaulting on treatment where family members were  allowed to collect medication in their absence had 2.5 times odds of defaulting compared to those who were not allowed to collect(p <0.05).Allowing family members to collect medications in place of the patient was found to be the independent risk factor for defaults with AOR of 2.1 & CI of 1.1-4.1). DOTS providers need to be trained and sensitized to follow and adhere with RNTCP guidelines for implementation of DOTS.

In the present study, there was a statistically significant association between cases (23.5%) and controls (8.1%) with respect to distance of treatment centre (p <0.05) and subjects who had to travel a distance of > 5 kms, in comparison to those who had to travel < 5 kms, had 3.49 times odd of defaulting on treatment (p <0.05).A case control study by Vijay S et al¹³ also found association of distance from treatment centre to be significantly associated with default. A prospective observational study by Chennaveerappa et al¹⁴ found distance from treatment centre as a reason for default. Study done by Slama K et al.¹⁰ where time was taken as a measure of distance to treatment centre and found that time needed for the patients to get to the TCU exceeding 30 minutes were 3.34 times more likely to default from treatment, than patients who were less than 30 minutes away. Considering the relationship between distance of the patients residence to DOTS centre, it is convenient to have DOTS centre within reach of the patient to improve adherence to DOTS.

Unsatisfactory attitude and behavior of DOTS provider, allowing collection of medicines by family members, distance more than 5 KM from treatment centre and disease not explained by DOTS provider were found to be the independent risk factors for defaulting on DOTS.

Current DOTS strategy under RNTCP should be strengthened further by undertaking appropriate measures addressing these risk factors and thus ensuring maximum adherence to treatment regimen.

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