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Factors associated with health-related quality of lifeamong pulmonary tuberculosis patients in Manila, the Philippines

Shoichi Masumoto Taro Yamamoto

Akihiro Ohkado Shoji Yoshimatsu

Aurora G. Querri Yasuhiko Kamiya

Accepted: 1 November 2013 / Published online: 22 November 2013

Springer Science+Business Media Dordrecht 2013

Abstract

Purpose Health-related quality of life (HRQOL) amongpulmonary tuberculosis (PTB) patients has not been

investigated in the Philippines. This study aimed to

describe HRQOL among PTB patients and to determine

factors that are associated with HRQOL.

Methods A cross-sectional survey was conducted at 10

public health centers and 2 non-government organization

clinics in District I, Tondo, Manila. Face-to-face interviews

using a structured questionnaire including Short Form-8,

Duke-UNC Functional Social Support Questionnaire, and

Medical Research Council (MRC) dyspnea scale were

performed with 561 PTB patients from September to

November 2012.

Results HRQOL among PTB patients was generally

impaired. Factors associated with lower physical compo-

nent summary were exposure to secondhand smoke (SHS)

(P = 0.038), positive sputum smear result (P = 0.027),

not working (P = 0.038), lower education level

(P\ 0.01), number of symptoms (P\ 0.01), number of

adverse drug reactions (ADRs) (P\ 0.01), higher score on

the MRC dyspnea scale (P\ 0.01), and low perceived

social support (P = 0.027). Lower body mass index

(P = 0.016), non-SHS exposure (P = 0.033), number of

symptoms (P\ 0.01), number of ADRs (P\ 0.01), lowperceived social support (P\ 0.01), and negative percep-

tion for waiting time in the clinic (P = 0.026) were iden-

tified to be factors significantly associated with lower

mental component summary.

Conclusion Socioeconomic status including SHS expo-

sure and low perceived social support, in addition to clin-

ical factors, may be associated with poor HRQOL. Further

study would be needed to assess our findings.

Keywords Tuberculosis Health-related quality of

life Secondhand smoke exposure Social support

Introduction

Tuberculosis (TB) continues to be a global public health

problem, with approximately 8.7 million incident cases and

1.4 million deaths in 2011 [1]. TB is the fifth highest cause

of morbidity and mortality in the Philippines, which is one

of 22 high-burden countries in the world [2]. Although the

case detection rate and treatment success rate have

exceeded the global target since 2005 after the initiation of

directly observed treatment, short-course (DOTS) [3], the

prevalence, and incidence of TB are still high. According

to the Global Tuberculosis Report 2012, the estimated

prevalence is 484/100,000 and the estimated annual inci-

dence is 270/100,000 as of 2011 in the Philippines [1].

Health-related quality of life (HRQOL) has recently

been evaluated as an outcome for many medical conditions

and refers to patient-reported physical, social, and mental

functioning. Although clinical and biological outcomes

such as case detection rate or treatment success rate have

been used as an indicator of TB control program, patient-

S. Masumoto (&)

T. Yamamoto

Y. KamiyaGraduate School of International Health Development, Nagasaki

University, 1-12-4 Sakamoto, Nagasaki, Nagasaki 852-8523,

Japan

e-mail: [email protected]

A. Ohkado S. Yoshimatsu A. G. Querri

Research Institute of Tuberculosis/Japan Anti-Tuberculosis

Association Philippines, Manila, The Philippines

A. Ohkado S. Yoshimatsu

Research Institute of Tuberculosis, Japan Anti-Tuberculosis

Association, Kiyose, Japan

1 3

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DOI 10.1007/s11136-013-0571-x


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reported outcomes such as HRQOL have not been well

investigated [4] and have been neglected when evaluating

outcomes of TB patients [5]. According to a systematic

review, Short Form-36 (SF-36) has been used most com-

monly to measure HRQOL in TB patients in past studies,

but the disease-specific instrument is not well established

[6]. Recent studies have shown that TB has a negative and

prolonged effect on HRQOL [710]. In addition, thepositive effect of treatment on HRQOL among TB patients

has been reported [11,12].

Factors associated with HRQOL among TB patients

have already been analyzed in several studies. Demo-

graphic characteristics: age, socioeconomic status: income,

education, housing condition, social security, disease-

related factors: white blood cell count, the number of

symptoms, and adverse drug reactions (ADRs) caused by

anti-TB drugs were indicated to be associated with

HRQOL among TB patients [7, 1315].

Tobacco smoking is well known as a risk factor for poor

treatment outcomes such as death [16], default [17], andrelapse after treatment [18]. It was reported that integrating

a smoking cessation program with DOTS had a positive

effect on the HRQOL of TB patients [19]. However, the

relationship between tobacco smoking and HRQOL has not

been evident. Therefore, scientific assessment of the rela-

tionship between tobacco smoking and HRQOL among TB

patients needs to be conducted.

Secondhand smoke (SHS) exposure is also a risk factor

for TB [20] and has been demonstrated to be related to

lower HRQOL among the general population [21] and

patients with heart failure [22]. However, the relationship

between HRQOL and SHS exposure among TB patients

has not been well documented. Because sidestream smoke

contains similar toxic substances as active smoking, SHS

exposure can have a negative effect on HRQOL among TB

patients.

Social support is assumed to be associated with HRQOL

among TB patients during treatment and is usually defined

as existence or availability on whom we can rely, people

who let us know that they care about, value, and love us

[23]. The relationship between social support and HRQOL

among TB patients has not been evaluated sufficiently.

Social support is expected to be a factor related to HRQOL

among TB patients because support from others, including

family members, is essential in completing long-term

treatment for TB.

HRQOL has not been well surveyed in TB patients in

the Philippines thus far. The objective of this study was to

investigate HRQOL among pulmonary TB (PTB) patients

and to determine factors that are associated with HRQOL

in Manila, the Philippines. The effect of tobacco smoking,

SHS exposure, and social support on HRQOL among PTB

patients was also analyzed.

Methods

Study design

A cross-sectional survey was conducted to describe

socioeconomic status, smoking status, HRQOL, and other

social factors among PTB patients, including both sputum

smear-positive and smear-negative patients, treated underDOTS.

Study area

The survey was conducted at 10 public health centers and 2

non-government organization (NGO) clinics providing

DOTS in District I, Tondo, Manila, where many socio-

economically deprived people live in a congested area. The

population is estimated to be approximately 410,000 in an

area of 5.64 km2 and 195,980 (47.8 %) accounts for the

underprivileged population.

Study population

Study participants were recruited from PTB patients who

were newly diagnosed or undergoing retreatment under

DOTS in District I, Tondo, Manila, between September

and November 2012. Patients with drug-resistant cases,

with extrapulmonary TB, with human immunodeficiency

virus, younger than 18 years of age, who were pregnant,

who were critically ill, or who had communication prob-

lems or severe complications such as cancer were exclu-

ded. All cases of PTB were diagnosed according to the

National Tuberculosis Control Program (NTP) guideline in

the Philippines [24].

Data collection

Recruitment was conducted by consecutive sampling of

PTB patients confirmed by the TB register except those

who were not eligible at each health facility. All patients

who were identified as having PTB and undergoing treat-

ment under DOTS were then recruited. Height and weight

were measured after completion of the interview, and body

mass index (BMI) was calculated. Patient interview using a

structured questionnaire was performed by 3 data collec-

tors. The structured questionnaire was designed to assess

the socio-demographic factors: working status, marital

status, monthly income, education level, alcohol drinking

habit, smoking habit, secondhand smoking exposure,

symptoms, and adverse drug reactions. On top of that, 3

instruments were included in the questionnaire to evaluate

HRQOL, social support, and severity of dyspnea. The

questionnaire was translated into Tagalog from the English

version using the forwardbackward translation method.

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Patients information about treatment was collected from

the TB register and NTP Treatment Card at the health

facilities.

Data collectors were recruited from local people and

trained for 2 days to conduct standardized interviews. A

pretest was conducted at one NGO clinic, which provides

TB Care Services to the urban poor in Payatas, Quezon

City, to confirm the feasibility, relevance, and validity ofthe questionnaire before full implementation of the study.

Instruments

Generic HRQOL (Short Form-8)

Short Form-8 (SF-8), a short version of SF-36, was used as

an indicator of HRQOL because of its brevity. Although no

study using SF-8 has been done to assess HRQOL of TB

patients, feasibility and reliability of SF-36 have been

validated in TB patients [25]. SF-8 uses one question to

estimate each of the 8 domains of SF-36 (GH: GeneralHealth, PF: Physical Function, RP: Role Physical, BP:

Bodily Pain, VT: Vitality, SF: Social Function, RE: Role

Emotional, and MH: Mental Health), which describe dif-

ferent aspects of HRQOL. The Physical Component

Summary (PCS) and Mental Component Summary (MCS)

are calculated by weighting each health domain scale score

and computing aggregate scores for each measure. Use of

the Tagalog version of the questionnaire was permitted by

Quality Metric Inc. Scores of each domain, PCS, and MCS

were calculated using scoring software provided by Quality

Metric Inc., into mean scores of 50 and standard deviation

(SD) of less than 10 in the 1998 U.S. general population.

The internal consistency of SF-8 was confirmed to be

sufficient by calculating Cronbachs alpha [26], which was

0.764.

Social support (Duke-UNC Functional Social Support

Questionnaire)

The Duke-UNC Functional Social Support Questionnaire

(FSSQ) was used to assess social support and has been

widely used to assess 2 areas: confidant support and

affective support [27]. The questionnaire consists of 8

items with a 5-point scale ranging from 1 (much less than I

would like) to 5 (as much as I would like). FSSQ scores can

range from 1 to 5, and higher scores reflect higher per-

ceived social support. In this study, scores were dichoto-

mized into low and high perceived social support group,

taking the 10th centile of the score as the cutoff point. To

the best of our knowledge, there is no definite cutoff score

in FSSQ. In the present study, the distribution of FSSQ

score was skewed to high score, so that FSSQ score of 3.5

(10 percentile in this study) seemed to be reasonable to

dichotomize into two groups. Cronbachs alpha of FSSQ

was 0.803, which shows high internal consistency.

Medical Research Council dyspnea scale

The Medical Research Council (MRC) dyspnea scale was

used to assess the severity of lung disease [28]. The MRCdyspnea scale consists of five statements about perceived

breathlessness. Patients are classified into 5 groups

according to how they perceived their disability. Grade 1

indicates the lowest, and Grade 5 shows the severest degree

of breathlessness.

Statistical analysis

Data were double entered into a Microsoft Access 2010

database and validated for any discordance. All statistical

analysis was conducted using STATA 12.1 (Stata Corp LP,

College Station, TX, USA). Scores of PCS and MCS weredealt as dependent variables. On the other hand, demo-

graphic factors: age, sex, BMI; information of treatment:

type of treatment, sputum smear result, treatment phase;

socioeconomic status: working status, marital status,

monthly income, number of people living together, edu-

cation level, alcohol drinking habit, smoking habit, sec-

ondhand smoking exposure; disease-related factors: the

number of symptoms, the number of ADRs; perception of

social support; severity of breathlessness; quality of ser-

vices: type of the clinic, time required to come to the health

center, waiting time, respect from health workers, cleanli-

ness of the facility, were dealt as independent variables. On

univariable analysis, each domain of SF-8 was analyzed

using Wilcoxon rank-sum test. PCS and MCS were ana-

lyzed using Students t test or analysis of variance. Dif-

ferences between groups were analyzed by chi-square tests

and Cochrane-Armitage tests. Multiple linear regression

models were constructed to determine factors associated

with PCS and MCS. Independent variables that were

related to dependent variables on univariable analysis

(P\ 0.20) were chosen to be analyzed in the multivariable

models. In addition, age, sex, treatment phase were also

included in multivariable analysis for adjustment. In mul-

tiple linear regression models, a backwardforward step-

wise selection procedure with a probability of 0.10 for

removal and a probability of 0.05 for entry was used to

identify associated variables. Variance inflation factor

(VIF) was calculated to assess multicollinearity in multi-

variable models [29]. Significance tests are 2 sided, with

P values of \0.05 considered statistically significant.

Results of multiple linear regression models are reported as

regression coefficients.

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Ethical considerations

The research proposal was reviewed by the Department of

Health Research Ethics Committee in the Philippines and

the Institutional Review Board of the Graduate School ofInternational Health Development, Nagasaki University,

and ethical approval was obtained from both institutions. In

addition, research permission was obtained from the

Manila City Health Department and each health center,

including 2 NGO clinics.

The study participants were informed of the overview

and the significance of the study as well as the risks and

benefits. Written informed consent was then obtained in

advance from each participant. Data obtained from the

study were maintained in the locked database and will be

kept for 1 year after the completion of the study.

Results

General

In total, 703 patients were identified by the TB register as

having PTB treated under DOTS. Forty-four of these

patients were excluded for shown reasons (Fig. 1). In total,

561 of the 659 eligible patients were interviewed, with a

Table 1 Demographic characteristics of study participants

Characteristics Mean

(SD)

n (%)

Age (years) 41.87

(15.6)

1830 166 (29.6)

3150 205 (36.5)5180 190 (33.9)

Sex (male/female) 367 (65.4)/194

(34.6)

Body mass index (BMI) (kg/m2) 19.65

(3.28)

\18.5 228 (40.6)

18.525 294 (52.4)

C25 39 (7.0)

Type of treatment, new/retreatment 421 (75.0)/140

(25.0)

Sputum smear, positive/negative 273 (48.7)/288

(51.3)

Treatment phase, intensive/continuation

230 (41.0)/331(59.0)

Occupation, working/not working 266 (47.4)/295

(52.6)

Monthly income (pesos)

\5,000 203 (36.2)

5,00010,000 220 (39.2)

[10,000 98 (17.5)

Missing 40 (7.1)

Marital status

Married 204 (36.4)

Single 157 (28.0)

Cohabitating 106 (18.9)

Widowed/separated 94 (16.7)

Family member 5.87

Education level

None 5 (0.9)

Elementary 180 (32.1)

High school 256 (45.6)

Vocational/college 120 (21.4)

Total years of education 8.35

Alcohol drinking

Never drinker 151 (26.9)

Former drinker 357 (63.6)

Current drinker 53 (9.5)

Smoking

Never smoker 236 (42.1)

Former smoker 274 (48.8)

Current smoker 51 (9.1)

Secondhand smoke exposure

Not exposed 242 (43.1)

Exposed 319 (56.9)

Symptoms C4 133 (23.7)

Fig. 1 Flowchart of the study participants. TB tuberculosis, PTB

pulmonary tuberculosis, DOTS directly observed treatment, short-

course,MDR multidrug-resistant. Treatment partner = A person who

gets medicine and conduct directly observed treatment

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response rate of 85.1 %. Ninety-eight patients could not be

recruited because they did not come to the health facilities

at the scheduled time for the following reasons: 1 patient

refused, 27 were working, 10 had treatment partners;

alternative person to get medicine for patients, 5 were

students, and 55 had unknown or other reasons (Fig. 1).

Comparisons of the subjects who were interviewed

(n = 561) and those who were not interviewed showed that

the participants were older than the non-participants (41.9vs. 36.7 years, P = 0.002), but no difference was seen in

sex distribution.

The demographic characteristics of the study partici-

pants (n = 561) are shown in Table 1. The mean age of the

participants was 41.9 years, and 65.4 % were male. The

BMI of 40.6 % of participants was less than 18.5 kg/m2,

which implies that underweight patients were prevalent at

the study site. In total, 25.0 % of the study participants

were undergoing retreatment. A total of 51.8 % of patients

with newly diagnosed PTB and 39.3 % of patients under-

going retreatment had positive sputum smears.

More than half of participants were not currently

working, and 36.2 % had income of less than 5,000 pesos

(%125USD) per month. Fifty-one patients (9.1 %) were

current smokers despite undergoing treatment for TB,

whereas 274 patients (48.8 %) were former smokers. With

regard to SHS exposure, 56.9 % of participants answered

that they were exposed to smoking in the household.

Similarly, 9.4 % kept drinking alcohol during treatment,

although 63.6 % were former alcohol drinkers.

The average scores of PCS and MCS were 44.5 7.7

and 46.0 8.0, respectively (Fig.2). Distribution of both

PCS and MCS was not skewed. Patients whose PCS and

MCS are less than 40, which indicate impaired function in

each dimension [30], accounted of 27.8 and 21.0 % of total

respondents, respectively.

Factors associated with HRQOL

Comparisons of component summary scores were con-

ducted for each independent variable, and the results are

shown in Table2. On univariable analysis, BMI less than

18.5 kg/m2 (P = 0.045), positive sputum smear result

(P = 0.023), not working (P = 0.018), monthly household

income less than 5,000 pesos (P\ 0.01), lower education

level (P\0.001), SHS exposure (P = 0.03), number of

symptoms (P\0.001), number of ADRs (P\ 0.001),

higher grade on the MRC dyspnea scale (P\ 0.001), and

low perceived social support (P = 0.035) were associated

with lower PCS. On the other hand, BMI less than 18.5 kg/

m2 (P = 0.014), monthly household income less than

5,000 pesos (P = 0.018), marital status of cohabitation

compared with single (P = 0.039), no SHS exposure

(P = 0.03), number of symptoms (P\ 0.001), number of

ADRs (P\ 0.001), higher grade on the MRC dyspnea

scale (P\ 0.001), low perceived social support

(P = 0.004), and negative perception to health workers

attitude (P = 0.04) were significantly associated with

lower MCS.

SHS exposure and SF-8

The younger population and female patients were more

frequently exposed to SHS on univariable analysis (mean

age was 43.4 years old in SHS non-exposed group versus

40.7 years old in SHS-exposed group, P = 0.02; 65.0 % of

female patients were exposed to SHS versus 52.6 % of

Fig. 2 Distribution of Physical Component Summary (PCS) and

Mental Component Summary (MCS) in Short Form-8. The average

scores of PCS and MCS were 44.5 7.7 and 46.0 8.0,

respectively

Table 1 continued

Characteristics Mean

(SD)

n (%)

Adverse drug reactions C4 188 (33.5)

Medical Research Council dyspnea

grade C3

98 (17.5)

Functional Social SupportQuestionnaire score B3.5 68 (12.1)

SD standard deviation

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Table 2 Comparisons of Short Form-8 component summaries by each independent variable

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male patients were exposed to SHS, P = 0.005). Table3

demonstrates the relationship between SHS exposure and

scale of each SF-8 domain, which shows that SHS-exposed

patients scored lower in the PF domain (P\ 0.001), and

reveals that SHS-exposed patients scored lower PCS

(P = 0.03). On the other hand, SHS exposure was signif-

icantly associated with a higher score on the MCS

(P = 0.03).

Social support and SF-8

On univariable analysis, younger patients (P = 0.12), male

patients (P = 0.076), and smoker (P = 0.047) tended to

have social support score ofB3.5. Low perceived social

support was significantly related to worse VT (P\ 0.001),

MH (P = 0.026), and RE (P = 0.047). Table4 shows that

low perceived social support was associated with lower

HRQOL, both on the PCS (P = 0.035) and MCS

(P = 0.004).

Multivariable analysis for HRQOL

Multiple linear regression models for PCS and MCS were

constructed. Forty-one questionnaires (7.3 %) had 1 or more

missing answers and were excluded from multivariable

analysis. On multivariable analysis, SHS exposure remained

significantly associated with lower PCS (P = 0.035). Posi-

tive sputum smear result (P = 0.025), not working

(P = 0.041), lower education level (P\ 0.01), number of

symptoms (P\ 0.01), number of ADRs (P\ 0.01), grade

on the MRC dyspnea scale (P\ 0.01), and low perceived

social support (P = 0.029) were significantly related to

lower PCS (Table 5). Low perceived social support also

remained significantly associated with lower MCS

(P\ 0.01). Low BMI (P = 0.02), number of symptoms

(P\ 0.01), number of ADRs (P\ 0.01), and negative

perception to waiting time in the clinic (P = 0.037) were

also identified as factors significantly associated with lower

MCS (Table5). In addition, SHS exposure remained asso-

ciated with higher MCS (P = 0.045). VIF was below 5 in all

independent variables in the models.

Discussion

The present study showed that the average scores of the

PCS and MCS of SF-8 were 44.5 and 46.0, respectively,

which demonstrated that HRQOL among PTB patients in a

socioeconomically depressed area is impaired compared

with the general population in the United States [30]. The

impaired HRQOL of PTB patients in this study is attrib-

utable to the effect of TB disease and socioeconomic fac-

tors. Factors that reflect the severity of TB disease, such as

number of symptoms and breathlessness, were strongly

associated with HRQOL both in physical and mental

aspects. These disease-related factors could be improved

along with the TB treatment. On the other hand, number of

ADRs was associated with lower HRQOL both in physical

and mental aspects. Compared with other disease-related

factors, ADRs can be managed by medical intervention to

Table 2 continued

PCSPhysical Component Summary, MCSMental Component Summary, SD standard deviationa Studentsttest

b Analysis of variancec Tukeys HSD test

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improve the patients HRQOL, and better management of

ADRs may have positive influence on treatment outcomesthrough the improvement of adherence. Levels of educa-

tion and monthly income had a substantial correlation with

HRQOL in the present study, which indicated that patients

with low socioeconomic status have a low perception of

HRQOL. These findings concur with the results of the

earlier studies [7, 8, 14], although these factors would be

difficult to modify. Having low BMI was also strongly

associated with low MCS, which suggests nutrition state is

associated with mental health of TB patients. In addition,

avoidable factors such as SHS exposure and lack of social

support were suggested to be associated with decreased

HRQOL. These findings suggest that HRQOL of TBpatients can be improved by intervention to such kinds of

social factors on an opportunity of getting TB.

Smoking has been reported to be a factor related to

worse HRQOL in the general population [3133], although

the relationship between smoking and HRQOL has not

been well documented in TB patients. In the present study,

no difference was detected in summary scores among

current smokers, former smokers, and never smokers. This

can be partly explained as a healthy smokers effect,

which means that those who have a good health status keep

smoking [9].SHS exposure in TB patients has not been well dis-

cussed compared with active smoking. Surprisingly, more

than half of the TB patients were exposed to SHS in the

household in the present study. Moreover, a negative effect

of SHS exposure on physical aspect of HRQOL was sug-

gested. The PF domain was affected significantly among

the 8 domains of SF-8, which implies that a direct negative

physical effect played a role in deteriorating PCS. In

contrast, a higher MCS was observed among the SHS

exposure group in the present study. An earlier study

reported that SHS exposure in the general population had a

negative effect on the mental aspect of HRQOL [21]. Thereason why this paradoxical result was obtained may be

explained by the influence of the MH domain, in which

there was a tendency for SHS-exposed patients to answer

positively. However, a causal relationship remains

unknown, and potential factors that were not measured in

this study might confound the association between SHS

exposure and the MH domain.

Women and the younger generation were likely exposed

to SHS exposure. Their family members should be

Table 3 Secondhand smoke exposure and Short Form-8 domains

Secondhand smoke Scale of answer in Short Form-8c P value

1 2 3 4 5 6

General Health Not exposed 28 (11.6) 52 (21.5) 103 (42.6) 48 (19.8) 11 (4.5) 0 0.19a

Exposed 46 (14.4) 69 (21.6) 143 (44.8) 46 (14.4) 13 (4.1) 2 (0.6)

Physical Function Not exposed 45 (18.6) 61 (25.2) 118 (48.8) 15 (6.2) 3 (1.2) \0.001a

Exposed 32 (10.0) 63 (19.7) 190 (59.6) 27 (8.5) 7 (2.2)

Role Physical Not exposed 48 (19.8) 85 (35.1) 75 (31.0) 20 (8.3) 14 (5.8) 0.21a

Exposed 71 (22.3) 90 (28.2) 78 (24.5) 60 (18.8) 20 (6.3)

Bodily Pain Not exposed 69 (28.5) 25 (10.3) 67 (27.7) 63 (26.0) 17 (7.0) 1 (0.4) 0.53a

Exposed 81 (25.4) 34 (10.7) 90 (28.2) 95 (29.8) 18 (5.6) 1 (0.3)

Vitality Not exposed 38 (15.7) 100 (41.3) 93 (38.4) 7 (2.9) 4 (1.7) 0.06a

Exposed 44 (13.8) 173 (54.2) 93 (29.2) 5 (1.6) 4 (1.3)

Social Function Not exposed 37 (15.3) 60 (24.8) 126 (52.1) 14 (5.8) 5 (2.1) 0.24a

Exposed 43 (13.5) 69 (21.6) 178 (55.8) 22 (6.9) 7 (2.2)

Mental Health Not exposed 36 (14.9) 79 (32.6) 96 (39.7) 29 (12.0) 2 (0.8) 0.19a

Exposed 57 (17.9) 110 (34.5) 119 (37.3) 30 (9.4) 3 (0.9)

Role Emotional Not exposed 43 (17.8) 56 (23.1) 110 (45.5) 23 (9.5) 10 (4.1) 0.92

a

Exposed 50 (15.7) 78 (24.5) 151 (47.3) 35 (11.0) 5 (1.6)

Physical Component Summary Not exposed 45.32 (7.60) 0.03b

Exposed 43.9 (7.72)

Mental Component Summary Not exposed 45.16 (8.06) 0.03b

Exposed 46.62 (7.89)

a Wilcoxon rank-sum testb Studentsttestc 1 is the best condition, and 5 or 6 are the worst condition in each domain

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encouraged not to expose patients in the household to

smoke. As indicated in the recommendation from the

International Union Against Tuberculosis and Lung Dis-

ease [34], it would be effective and efficient to integrate

smoking cessation counseling for patients and their family

members with usual health education for TB patients. Such

approach may contribute to improve ones HRQOL even

after treatment.

Social support was associated with the physical and

mental aspect of HRQOL among PTB patients in the

present study. This result is consistent with an earlier

finding that closer relationship with family members and

friends is correlated with better HRQOL [14]. Patients with

low perceived social support tended to be younger and

were negatively affected especially in VT, MH, and RE,

which may suggest that they lost motivation to join social

activities. In addition, impaired mental health might lead to

decreased perception for physical aspect of HRQOL as a

consequence. For such patients, it can be helpful to

encourage them to join peer groups or community groups.

Moreover, social workers, whom patients can consult about

mental problems including economic matters, are desirable

in health centers.

The present study has several limitations. First, SF-8 has

not been sufficiently evaluated in the general population in

the Philippines; hence, the results of SF-8 have to be

interpreted carefully. Because cultural differences may

threaten the validity of the questionnaire, normative data

for the Filipino population will need to be assessed. Sec-

ond, this was a cross-sectional study, so it is difficult to

determine the causal relationship. Third, the study was

conducted in an economically deprived urban area in

Manila, and it would be difficult to generalize the results

because this area has special circumstances. Fourth, com-

parisons of the subjects who were interviewed and those

who were not interviewed showed that the participants

were older than the non-participants. This difference might

lead to selection bias, but might not influence the result.

Finally, the present study was conducted through face-to-

face interviews, which may result in misclassification of

smoking status, alcohol drinking habit, and SHS exposure

due to social desirability bias. It is well known that patient-

oriented data about smoking status tend to be underesti-

mated [35]. In this study, we were not able to measure

biomarkers such as serum cotinine or exhaled carbon

monoxide concentration for validating smoking status of

Table 4 Social support and Short Form-8 domains

Functional social support

Questionnaire

Scale of answer in Short Form-8c P value

1 2 3 4 5 6

General Health B3.5 7 (10.3) 14 (20.6) 28 (41.2) 17 (25.0) 1 (1.5) 1 (1.5) 0.25a

[3.5 67 (13.6) 107 (21.7) 218 (44.3) 76 (15.4) 23 (4.7) 1 (0.2)

Physical Function B3.5 8 (11.8) 10 (14.7) 42 (61.8) 6 (8.8) 2 (2.9) 0.11a

[3.5 69 (14.0) 114 (23.2) 266 (54.1) 35 (7.1) 8 (1.6)

Role Physical B3.5 9 (13.2) 23 (33.8) 18 (26.5) 13 (19.1) 5 (7.4) 0.11a

[3.5 110 (22.4) 151 (30.7) 135 (27.4) 67 (13.6) 29 (5.9)

Bodily Pain B3.5 14 (20.6) 7 (10.3) 17 (25.0) 24 (35.3) 5 (7.4) 1 (1.5) 0.09a

[3.5 136 (27.6) 52 (10.6) 139 (28.3) 134 (27.2) 30 (6.1) 1 (0.2)

Vitality B3.5 4 (5.9) 25 (36.8) 33 (48.5) 4 (5.9) 2 (2.9) \0.001a

[3.5 78 (15.9) 247 (50.2) 153 (31.1) 8 (1.6) 6 (1.2)

Social Function B3.5 8 (11.8) 16 (23.5) 35 (51.5) 6 (8.8) 3 (4.4) 0.36a

[3.5 72 (14.6) 112 (22.8) 269 (54.7) 30 (6.1) 9 (1.8)

Mental Health B3.5 8 (11.8) 19 (27.9) 28 (41.2) 12 (17.6) 1 (1.5) 0.026a

[3.5 85 (17.3) 170 (34.6) 186 (37.8) 47 (9.6) 4 (0.8)

Role Emotional B3.5 8 (11.8) 16 (23.5) 27 (39.7) 16 (23.5) 1 (1.5) 0.047

a

[3.5 85 (17.3) 118 (24.0) 233 (47.4) 42 (8.5) 14 (2.8)

Physical Component

Summary

B3.5 42.67 (7.44) 0.035b

[3.5 44.77 (7.70)

Mental Component

Summary

B3.5 43.38 (8.19) 0.004b

[3.5 46.35 (7.90)

a Wilcoxon rank-sum testb Studentsttestc 1 is the best condition, and 5 or 6 are the worst condition in each domain

Qual Life Res (2014) 23:15231533 1531

1 3


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participants. SHS exposure can be misclassified as well,

though a linear correlation was shown between self-

reported SHS exposure and biomarkers such as salivary or

serum cotinine [36,37].

To overcome these limitations, SF-8 needs to be vali-

dated in the general Filipino population. Subsequently, a

well-designed study such as a cohort study is needed to

confirm the causal relationship between each factor and

HRQOL.

Conclusions

A cross-sectional survey was conducted to describe

HRQOL among PTB patients in Manila, the Philippines.

This study provided basic information about HRQOL

among PTB patients and identified the factors associated

with HRQOL in an economically depressed area in the

Philippines, which could be a relevant reference for pos-

sible policy change in the National Tuberculosis Control

Program. In addition to clinical factors, socioeconomic

status such as working status and education level was

associated with physical aspect of HRQOL. On the other

hand, clinical factors, BMI, and waiting time in the clinic

were related to mental aspect of HRQOL. Especially, SHS

exposure and social support seemed to be significant andmodifiable factors associated with both physical and

mental aspects of HRQOL.

Acknowledgments We appreciate the support of the technical and

administrative staff of RJPI and cooperation from staff in each health

center and NGOs. In addition, we wish to thank Dr. Pasquala Agujo,

Chief of Division of TB Control; Dr. Romeo Cando, District Health

Officer; and Ms. Gloria Inocencio, District Supervisor/NTP Nurse

Coordinator; Dr. Armie Vianzon, NTP Medical Coordinator, for

arranging and helping in the implementation of data collection. We

also wish to thank all patients who participated in the study, and

research assistants who conducted interview. This study was con-

ducted as a research for master thesis of first author and funded by

Graduated School of International Health Development, NagasakiUniversity.

Conflict of interest None declared.

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