Tuberculosis is a common and infectious communicable disease that is caused by mycobacterium tuberculosis. It is of two principle kinds: pulmonary TB, which usually attacks the lungs, and extra-pulmonary TB, which attacks any part of the body, such as: the lymphatic, pleural, bone and/or joint, genitourinary, miliary, peritoneal, meninges and/or central nervous system (CNS), and all other sites combined. Pulmonary TB sometimes combined with extra pulmonary tuberculosis (Parimon, 2008; Sreeramareddy et al., 2008; Friedman, 2001).
Tuberculosis is spread in form of droplets which are expelled when the infected persons cough, sneeze, speak, or sing. Close, prolonged, frequent, or intense contacts are the main ways that leads to 22% of the infection rate. Other resources include: foreign-born from areas where TB is common, residents and employees living in plagued congregate settings, health care workers who serve severely infected clients, low-income populations, highly inflicted racial or ethnic minority populations, children exposed to severely infected adults, and persons who inject illicit drugs.
Extra pulmonary TB that occurs outside the lungs may spread through lymphatic or hematogenous dissemination to any tract or through coughing and swallowing to the gastrointestinal tract. Such a type of bacteria may remain dormant for years at a particular site before causing the disease. Since extra pulmonary TB can affect virtually all organs, it has a wide variety of clinical manifestations. A matter which causes difficulty and delay in its diagnosis (Mehta, 1991; Gonzalez et al., 2003). Though, it is said to be more often diagnosed in women and young patients (Rieder et al., 1990; Gonzalez et al., 2003; Yang et al., 2004; Noertjojo et al., 2002; Cowie and Sharpe, 1997; Antony et al., 1995; Chan-Yeung et al.,2002). In the United States, extra pulmonary TB is associated with ethnic minorities and with those born in other countries (Rieder et al., 1990) while in Asia, lymphatic TB occupies the front position of the risky infectious diseases (Cowie and Sharpe, 1997, 1998; Moudgil and Leitch, 1994; Nisar et al., 1991; Ormerod, et al., 1991). A study of Somali TB patients in Minnesota showed frequent lymphatic TB as well (Kempainen, et al., 2001). In HIV-infected patients, the frequency of extra pulmonary TB depends on the degree of decrease in cellular immunity (Huebner and Castro, 1995; Barnes, et.al., 1991). While in patients with <100 CD4 cells/mL, extra pulmonary and disseminated TB counts for 70% of all forms of TB (Jones, et al., 1993). The materials needed for culture confirmation of extra pulmonary TB is much more difficult than that for culture confirmation of pulmonary TB (Gonzalez, et al., 2003).
Economic and Social Effect of Tuberculosis
Statistically speaking, Mycobacterium tuberculosis infects one-third of the world’s population and is the most common single death causing agent in young adults (WHO, 2008). Globally, it accounts for 2.5% of the other diseases. However, the consequences of tuberculosis (TB) on society are huge. Worldwide, one person out of three is infected with Mycobacterium tuberculosis, i.e. two billion people in total. Currently, it holds the seventh place in the global ranking of the causes of death. (Dye, 1999; Smith, 2004).
Economically speaking, TB hinders socioeconomic development for the high percentage of the disease, 75%, afflict the productive age group that ranges between 15-54 years. Furthermore, ninety-five per cent of all cases and 99% of deaths occur in developing countries, with the greatest burden in sub- Saharan Africa and South East Asia (Dye, 2006; World Health Organization, 2006a).
Despite the availability of Effective drugs for more than 50 years, every 15 seconds, someone dies from TB. Besides, the percentage of TB infection is every second of every day (Dye, 2005; WHO, 2000). In light of this, Dye (1999) and Smith (2004) add that unless intensive efforts are made, it is likely to maintain that position through to 2020 and it is likely for a person with active TB to infect an average of 10 to 15 other people every year.
The total Budget for TB control in 22 severely-infected countries in 2006 equals US$ 1.6 billion, taking into consideration the cost of the health system staff, the infrastructure used for TB control, in addition to the requirements of the National Tuberculosis Control Programme which is less than that of 2002 which soared to US$ 876 million. However, the Russian Federation and South Africa occupy the front position as far as TB costs are concerned, where their costs amounted US$ 810 million. However, even though the health systems managed to control the growing number of TB patients in 2006, TB financial costs in 2006 would have been the same as for the National Tuberculosis Control Programme budgets, i.e. US$ 141 million. Furthermore, such costs and such funding gaps are liable to be increased to US$ 2.0 billion, and US$ 180 million, respectively when all 74 infected countries are included. Globally, these 74 countries represent 89 % of TB cases (Dye, 2006; World Health Organization, 2006a). On the other hand, WHO estimates that 9.27 million new cases of TB occurred in 2007 (139 per 100 000 population), compared with 9.24 million new cases (140 per 100 000 population) in 2006 and with 44% or 4.1 million (61 per 100 000 population), were new smear positive cases.
As far as the expected cost for diagnosing and curing this disease is concerned, it is of three kinds: the direct, indirect and the intangible costs, and as stated below:
Direct or immediate costs for diagnosing and treating are of importance for poor families. (Lubeck, 2003; Verstappen, 2004; Drummond et al., 2005) state, in this respect, that direct costs include the costs of medical care and related items, such as: the expenses of visiting doctors, laboratory and radiological examinations, hospital costs, medications, transportation to and from the doctors, and special aids.
A great economic loss occurs as a result of “indirect” costs, which involve the cost stemming from losing employees, traveling to health facilities, selling assets to afford TB treatment, and in particular, losing productivity due to illness and premature death (Smith, 2004; Floyd, 2003; World Health Organization, 2005a). In light of this, Johannesson (1996) indicates that indirect costs are “those resulting from the loss of function in one’s usual activity, including work disability, sick-leave or reduced productivity”.
In calculating the loss of productivity, the two commonly used methods are the human capital and the friction cost approach. The human capital approach evaluates the individual’s productivity by the market price; that is the potential gross salary of the individual, including all of the employer’s contributions. While in case of self-employed persons, the gross personal income includes the statutory insurance expenses or as Lofland et al. (2001) puts it, it takes a societal approach. The friction cost approach assumes that the disabled person is replaced by a currently unemployed person during the friction period, where the latter is the time during which the sick person is replaced. Hence, friction costs include all the expenses related to replacing that worker (ibid.).
The estimated cost of TB treatment in patients with susceptible tuberculosis in developed countries ranges from US$ 276 to US$ 1546 and for multi-drug resistant tuberculosis (MDR-TB) ranges from USD 1000 to 10000. (Wyss & Lorenz, 2001, and WHO 2000). Determining the approximate costs for effective tuberculosis control is an important factor in specifying the actual expenditures required for treating tuberculosis. A matter that could be achieved by taking into consideration both the direct and indirect costs of tuberculosis.
Lubeck (2003) and Xie et al. (2008) maintain that intangible costs can be defined as the pain and suffering of a patient because of the disease. It includes a reduction in the physical function, an increased psychological distress, and a reduced social function. Intangible costs can be measured either by HRQoL questionnaires or alternatively by a contingent evaluation method which is based on “eliciting the levels of willingness in paying”.
Lienhardt et al. (2001) add that tuberculosis has a severe impact on the impoverishment of patients and their households. The major factors which lead to impoverishment involve the following: the inability to work due to illness, the direct and indirect costs of accessing diagnosis and treatment, and the repeated visits to different care providers, which are associated with providers and patient’s delays.
DOTS have the potentiality to reduce the economic and social effect of TB for patients and their households. However, few studies have explicitly examined this issue. The study in Uganda by Saunderson (1995) found that under DOTS, patient costs were reduced and they were able to start working again quickly.
In South India, Muniyandi et al. (2008) conducted a comparative study to calculate the costs of treating TB patients, using DOTS programme with those who were treated without using such a programme. The total number of patients was 896, divided as such (455 for DOTS and 441 for non-DOTS). Throughout the study, it was found that the direct cost for patients registered in DOTS areas, and for the mean pre-treatment was significantly lower than that in non-DOTS areas (Rs 874 vs. Rs 1,064) and that the mean direct costs during the treatment were also lower than that of the former (Rs 227 vs. Rs 250).
Pre-treatment indirect costs were nil in Rs 951 in the DOTS area compared to Rs 1,895 in the non-DOTS area. Throughout treatment, the indirect costs were significantly less in DOTS than in those of the non-DOTS (Rs 825 DOTS vs. Rs 1,821 non DOTS). As for the total mean cost of pre-treatment direct cost, it was lower in DOTS, Rs 1,762 than in non-DOTS area, Rs 2,903. The total mean of the direct costs during the treatment was also lower in DOTS, Rs 1,014, in comparison to Rs 2,069 in non-DOTS. Generally speaking, the indirect costs were significantly lower in the DOTS area than in non-DOTs ones.
Sreeramareddy et.al. (2008) conducted a retrospective study for about 474 patients in a tertiary care hospital that lies in Western Nepal for the purpose of comparing demographic, life-style and clinical characteristics between EPTB and PTB patients. The study found that the ratio of males to females was 1.07 (119/111) in EPTB and 2.29 in PTB (170/74), and that the median age of EPTB patients (29.5 years) is much lower than that of PTB patients, (47.5 years). Further, the study stated that, in the past, smoking and immunosuppressive drugs like steroids or anti-cancer drugs, diabetes and TB were mostly and directly related to PTB.
Studies from a number of developing-countries revealed that the poor have much less access to TB and DOTS programmes than the non-poor, to the extent that they can be excluded from TB care (Singh et al., 2002; Balasubramanian et al., 2004). Cohen et al. (1999) carried out three studies to examine the association of several markers of social status (unemployment, perceived and observed social status) with the host resistance to upper respiratory infections. The study found that unemployment and lower social status were associated with the increased susceptibility to infection. Such an association proves the fact that the grave impact of this disease occurs in the lowest social status groups. Thus, the further the increase in social status, the more decreases in susceptibility.
Portero, et al. (2002) noticed that there is a relationship between being healthily uneducated and the percentage of TB infection among the general population of Metro Manila, Philippines. That is, a lower score was found to represent the general knowledge about TB while a higher score was independently associated with college education. On the other hand, the low monthly-paid persons were characterized by having no TB knowledge; no intention of seeking health care and by no self-treatment of TB. Schoeman et al. (1991) studied the relationship between the socioeconomic factors and pulmonary TB. By measuring variables, like: demographic details, general living conditions, household ownership of luxury items, and weekly consumption of four proteins (meat, fish, chicken and cheese). They concluded that no significant differences were found between cases and controls on most of the variables, and that the overall significant differences were on the pattern of language groups, employment and meat and chicken consumption. Such a tendency was observed for more employed cases than for the controls, who are of primary school education. However, no conclusive evidence was found on the association between socioeconomic factors and the risk of developing TB.
Gustafson et al. (2004) studied the impact of demographic, socioeconomic and cultural risk factors on active TB in Guinea, Bissau. They found that Bissau has a very high incidence of intra-thoracic TB. Factors as the human immunodeficiency virus (HIV), increasing age, male sex, ethnicity, adult crowding, family structure, and poor housing conditions were independent risk factors for TB. Apart from HIV prevention, TB control programmes need to emphasize risk factors, such as: the socioeconomic inequality, ethnic differences, crowding, and gender.
Souza et al. (2000) identified that socio-demographic risk factors are statistically associated with TB in Brazil, within “defined population bases” (i.e. populations living in areas with well-defined boundaries). A matter which makes it possible to construct different levels of aggregation, including census tracts, neighborhoods, and sanitary districts. The results, further, showed that the distribution of such a disease at the census-tract level is not aggregated randomly. The results also involved the need for additional ways of stratifying this population and expressing different collective levels TB risks. The results, furthermore, indicated that there were high percentages of households without satisfactory sanitary installations and without regular garbage collection, in addition to noticeable percentages of illiteracy among persons aged between 10–14 years and among extremely limited schooling heads of family.
Floyd et al. (1997) conducted a study in rural South Africa to compare the cost-effectiveness of (DOT) with conventionally delivered treatment for tuberculosis. Conventionally, the patients were stayed in the hospital for the first two months of treatment to ensure compliance with treatment during the intensive phase. But, throughout their study, they found that the directly observed treatment was 2.8 times cheaper to deliver than that of the conventional treatment (US 4740.90 compared with US$ 2047.70) and that it was more cost-effective, costing US$ 890.50 per cured patient compared with either US$2095.60 (best case) or US$3700.40 (worst case) of the conventional treatment.
The analytical study of Cost-effectiveness was done by Sanderson (1995) in Uganda to estimate the total costs borne by the patient and the health service for different treatment program designs. The study concentrated on two regimens (designs) of treatment: the first one is currently used and consists of two monthly hospitalized initial phase then four to ten months continuation phase. The other regimen consists of four non-hospitalized months, weekly supervision and of blister usage in the initial phase while the continuation phase is as the current used regimen.
The study found that the design based on an ambulatory treatment of patients without hospitalization is costlier than that depending on hospitalization during the initial phase (current regimen) which equals ? 115.23 and ? 190.09, respectively. The study also measured the cost for patients to be approximately 70% of the cost of the current used regimen (i.e., before diagnosing, during hospital stay, the lost work time and the social cost).
Another study of cost effectiveness was carried out by David & Daniel (1999) in California during 1995 to compare between self-administration therapy (SAT) and directly observed treatment (DOT) for patients of less risky TB. They estimated that the rate of treatment default was 1.7%. The study found that SAT has more cost effectiveness than DOT. The total cost of SAT is less than DOT by US$ 1.83 million, excluding the cost of patients out of pocket money, the time of work lost, diagnosis and out of hospitalization.
Muniyandi et al. (2005) conducted another study to see the economic impact of TB in Tamilnadu, India during June and December 2000, to assess the expenditures incurred due to TB whether direct medical, non-medical, indirect and the total costs before and during the treatment and to specify the effect of such a disease on employment. The study arrived at the following fact that the median direct, indirect and total costs for 343 patients who completed their treatment successfully were Rs 340. During treatment, the direct costs, Rs 100, were more than 50% from patients who did not get any indirect costs in both pre treatment, and during treatment periods. Moreover, the total costs were Rs 1398. In other words, patients have lost about 12%, i.e. more than 60 workdays.
In (2009) Kik et al. conducted another comparative study to compare the direct and indirect costs of pulmonary and extra pulmonary 60 immigrant TB patients in Netherlands, and specifically, at the 14 Municipal Health Services (MHSs) and the two specialized TB hospitals from April 2007 to October 2007. In the course of the study, they did not observe any significant differences between the characteristics of the interviewed patients of PTB and ETB though ETB patients tended to be older than PTB patients. The expenditures of patients varied widely. For instance, the direct costs during the entire TB illness averaged €353 (median €190); the total direct costs of patients ranged from €0 to €3961; and the costs during the pre-diagnostic period were slightly higher for patients with ETB (mean €10, sd 18.8) than that with PTB (mean €3, sd 7.4, ). Most of the costs were incurred if patients were hospitalized, and in case of indirect costs, the average patients lose 81 days of their normal productivity due to TB infection (i.e. a median of 60 days) where ETB patients, on average, lose much time during the pre-diagnostic period than those of PTB patients.
Dejonghe et al. (1992) evaluated the direct cost effectiveness of standard and short-course treatments for the smear positive TB patient in Malawi, Mozambique and Tanzania and found that short-course chemotherapy with hospitalization is approximately 23% cheaper according to the heath services perspectives than the standard treatment and that by implementing the ambulatory short-course of treatment, the cost of treatment will be reduced to 35%, 65%, and 50%, in Malawi, Mozambique, and Tanzania, respectively.
Brown et al. (1991) estimated, in the united states, the total expenditures of health care for the patient, inpatient diagnosis and treatment, screening, preventive therapy, contact investigations, surveillance and for the outbreak investigations of tuberculosis. Throughout the study, which involved 26, 283 cases, they estimated that 90% of the patients were given an outpatient treatment (23,654 TB cases) and that the direct medical expenditure for TB was approximately US$ 703.1 million. From that, only US$ 423.8 million represented the cost of inpatient care whereas US$ 182.3 million represented the outpatient care. The study depended on estimation to count the total costs for drug resistant (10.7%) and for multi-drug resistant tuberculosis (3.5%) while the indirect cost of illness was excluded.
Wyse & Lorenz (2001) conducted a study, in Dar es Salaam, Tanzania, on the costs of tuberculosis for households and health care donors. This study included one hundred ninety-one patients with a treatment period ranging from 8-to-12 months. They found that the average costs to a patient range from US $ 186 to US $ 1457 (including costs such as the following: x-ray examinations, laboratory, consultation, drug, hospitalization, transportation and productive loss costs) and that the average costs to the health care donors per patient was only US $ 90 (including programme management, laboratory unite, drug and ambulatory care cost). The known major types of costs in the study were the costs of drugs, costs transportation and, in particular, the costs due to the loss of work force.
A cost effectiveness study, in Pakistan, was conducted by Khan et. al. (2001); the study lasted from Sep. 1996 until June 1998 for the purpose of finding out the most cost effective strategy for the implementation of direct observed treatment (DOT). Throughout the study, the patients were divided into three different groups according to the type of the DOT used strategy, such as: self administration of medication, DOT by family members or DOT by health care workers. The results illustrated that the type of self-administration DOT was themost cost-effective. Its costs soar high to US $ 164 per patient cured compared to the other strategies as DOT with family, and DOT with healthcare worker where their costs were US$ 172 and US$ 310, respectively.
A pharmacoeconmic evaluation of tuberculosis was conducted by Elamin et.al. (2008) in Penang, Malaysia. The number of patients was 202 with a treatment period ranging form 6-to-12 months. The study found that the average cost to the healthcare providers per patient was only US $ 189.5 (including x-ray examination, laboratory tests, consultation cost, drug and supplies, health staff time, hospitalization costs, stationary, and over head cost). Furthermore, the average costs to the patients was US $ 726.90 (including meals, transportation and the time away from work). The major types of costs documented in the study were drug and supplies, transportation and, in particular, the cost due to the loss of work forces
Further cost-effectiveness study was carried out by Islam et al. (2002) in Bangladesh to compare the cost-effectiveness of TB programme run by the Rural Advancement Committee (RAC), which used community health workers (CHWs), with that of the government TB programme which did not use CHWs. Such a study identified a total of 186 and 185 TB patients over one year to find that the application of CHWs was more cost-effective than government area, which obtained a cure rate at 84%, i.e. US$ 64 per patient compared with 82% cure rate, i.e. US$ 96 per patient in the governmental areas.
Rajeswari et al. (1999) conducted a study on the socioeconomic impact of TB on patients and families in India to assess the expenditures involved in tuberculosis diagnosis and treatment; the effect of tuberculosis on patient’s family and to estimate the loss of income due to work disability. The study included that a total of 304 patients, who received their treatment from private practitioners, governmental and non-governmental hospitals. The expenditure cost included direct medical cost, such as: consultation fees and the money spent on investigation and drugs; direct non-medical cost, such as the money spent on transportation, loading, special food and on persons accompanying the patients; and indirect cost, as the loss of wage and the decreased earning ability due to illness. They found that the direct cost in the three different types of health facilities was US$ 38.5, US$ 48.5 and US$ 253.00, and that the total cost of TB treatment was US$ 147.50, US$ 169.50 and US$ 368.50 in the governmental hospital, non-governmental hospital and private practitioners, respectively.
Health Related Quality Of Life (HRQL)
Carr et al. (1996) stated that the broad-ranging concept, the quality of life (QoL), incorporates health states, satisfaction with work, leisure time, level of independence, social relationships, and environment. The World Health Organization (WHO) defined QOL as the ability of individuals to perceive their position in life within the cultural contextual and the valuable systems in which they live by in accordance with their goals, expectations, standards and concerns (Anonymous 1995). According to Khanna and Tsevat (2007), HRQoL is a multi-dimensional concept that associates the physical, emotional, and social components of an individual with his/her medical conditions or treatment).
In recent decades, the interest of measuring HRQoL has increased noticeably due to advances in medical science and technology and to the increased number of people who live contentedly with chronic diseases and disabilities. According to the patients’ perspective, the change in the morbidity profile evoked the need of evaluating the outcome of different treatments.
Measuring HRQoL can be done either by disease-specific tools or generic measurement tools. The generic instruments allow comparisons between patient groups with different diagnoses, whereas the disease-specific instruments give information about only one certain disease and its effect on health. Disease-specific instruments are, however, more sensitive to the important differences in health status. They are; therefore, successfully used for measuring results of specific treatments. A well-known example of a disease-specific instrument is the questionnaire of Rheumatoid Arthritis Quality of Life (RaQoL). It is the first patient-completed instrument, especially designed to be used with RA patients (de Jong et al. 1997). Other example of a disease-specific instrument is the questionnaire of Tuberculosis Quality of Life (SF-12 Questionnaire by Dhingra and Rajpal 2003).
The generic instruments are divided into two kinds: profile and single index score measures, as illustrated below:
- Profile measures describe the health state according to various physical and emotional dimensions, such as physical functioning, bodily pain, general health, social functioning, and other dimensions. A well-known example of it is the widely used a Health Status Survey Questionnaire resulted from a Medical Outcomes Study of a Short Form with 36 items, (SF-36).
Ware and Sherbourne (1992) mentioned that SF-36 is a well-validated generic health status measure used in health surveys of both general and various populations with different diseases. The 36 items in the questionnaire are grouped into 8 multi sub-scale items that measure the physical functioning; role limitations due to physical problems and bodily pains; general health perceptions; vitality; social functioning; mental health; and role limitations due to emotional problems. For each subscale, there is a score that calculates values from 0 to 100, where the low scores indicate poor health.
Chamla (2004) prospectively measured active TB patients’ HRQL at the start point, middle, and at the end point of the treatment. During the treatment, role physical, vitality and mental health scores decreased after the initial 2 months, but showed an overall improvement at the end of the treatment while all the other subscale scores showed a gradual increase throughout the treatment. After the anti-TB treatment, the study observed a significant improvement in all physical health subscales of the SF-36 (physical problems and bodily pains; general health, p < 0.05), besides two mental health subscales role limitations due to emotional problems and social functioning (p < 0.05) improved significantly. The study also observed that, at the end of the treatment, active TB patients still significantly scored lower at role physical, vitality and mental health subscales compared to general population comparisons. Generally speaking, physical health subscales were more affected than mental ones. Furthermore they found that younger people tended to have better HRQL than older ones.
Two studies, in Canada at the Montreal Chest Institute, a TB clinic, were conducted by Dion et al. (2002, and 2004); the studies compared, in three consecutive interviews, between patients who had already begun treating active tuberculosis (three consecutive interviews during the intensive phase), people with LTBI and people had previously been treated from TB disease, the studies noticed that the active TB patients scored significantly lower in SF-36 physical Component Scores, but not in Mental Component Scores, when compared to people with LTBI and those with previously treated TB disease.
Wang et al. (1998) maintained that active TB patients reported lower scores (p < 0.01) across all SF-36 subscales than the healthy non-TB people, whose role of physical and role of mental are most affected. Guo et al. (2008, 1998) stated that, in comparison to those with LTBI, people with active TB scored significantly lower at all SF-36 subscales. In contrast, SF-36 scores among people with LTBI before taking the preventative therapy were very similar to that of U.S. norm references. In addition they found that older people tended to have poorer HRQL than younger ones.
Marra et al. (2008) identified areas of HRQL that are affected by LTBI and active TB disease, the study included the patients with recently diagnosed active TB (104) or LTBI (102)patients , the Short Form-36 (SF-36) at baseline, 3 months, and 6 months were administered. The study analyzed the differences in HRQoL of both Latent TB and Active TB infection and discovered that, in comparison to those with LTBI, people with active TB scored significantly lower at all SF-36 subscales, in the onset of treatment. In contrast, SF-36 scores among people with LTBI before the preventative therapy were very similar to that of U.S. and after 6 months of drug therapy, the study noted a significant HRQL improvement in active TB patients throughout the 6 months of treatment, using SF-36. Although anti-TB treatment was generally improved HRQL, active TB patients still had poorer HRQL in Physical Component Scores and Mental Component Scores at the end of the treatment, compared to the LTBI and general population. The study added that, after the preventive treatment, Mental Component Scores among people with LTBI declined significantly, while Physical Component Scores stayed unchanged.
Study in the Ankara, Turkey was conducted by Aydin and Ulusahin (2001); they compared the TB patients with COPD patients and the study found that TB patients had a lower prevalence of depression and anxiety and a lower level of disability. The study assumed that the chronic duration of COPD and the older age of the COPD patients may lead to a higher prevalence of psychological impairments, and that with multi-drug resistant, TB patients reported to have the worst disability level.
Yang et al. (2003) indicated that pulmonary TB patients showed more psychological symptoms and a lower degree of social support in comparison to healthy controls. Moreover they observed that males were more likely to have better health than females.
Duyan et al. (2005) found that the best HRQL correlated with variables like: the higher income, education, better housing conditions, better social security, and with closer family’s and friends’ relationships. Further addition the study found that there were no significant associations between gender, age and HRQL in TB patients
HRQoL assessment study for pulmonary TB and LTBI patients in Tarrant County in the United State was performed by Pasipanodya et al. (2007); they measured HRQL among pulmonary TB, who completed at least 20 weeks of the treatment period. They discovered that, in comparison to those with LTBI, treated TB patients had lower scores and that lung functions and/or those born in the United States (against foreign born) tended to have better HRQL outcomes. Moreover, no gender and smoking difference were noted.
Rekha et al. (2009) evaluated HRQoL of pulmonary TB in Chennai, India; the study noted that the HRQoL in TB patients in terms of symptom, a
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