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Prevalence of and risk factors associated with latent tuberculosis in Singapore: A cross-sectional survey

Open AccessPublished:May 11, 2018DOI:https://doi.org/10.1016/j.ijid.2018.05.004

      Highlights

      • An overall latent tuberculosis prevalence of 12.7% was found amongst Singapore residents.
      • There was a wide variation in positivity rate based on the participants’ country of birth.
      • Risk factors include age, education, socio-economic status, and alcohol usage.

      Abstract

      Objectives

      This first cross-sectional survey on latent tuberculosis infection (LTBI) in Singapore was performed by utilizing the QuantiFERON Gold In-tube (QFT-GIT) assay to collect data on the prevalence of LTBI and to identify potential risk factors associated with LTBI.

      Methods

      Nationwide household addresses were selected randomly for enumeration, and Singaporeans or Permanent Residents aged 18–79 years were identified. One eligible member per household was selected using the Kish grid. Each participant answered a questionnaire assessing their medical history (including tuberculosis (TB)), socio-economic factors, and lifestyle factors. They also provided a blood specimen for the QFT-GIT assay. Participants with a positive QFT-GIT result were defined as having LTBI if they were asymptomatic. To identify independent risk factors, adjusted hazard ratios were obtained using the multivariable modified Breslow–Cox proportional hazards model.

      Results

      An overall QFT-GIT positivity rate of 12.7% was detected amongst 1682 Singapore residents. There was a wide variation in the positivity rate according to the participants’ country of birth. Higher LTBI prevalence was also significantly associated with increasing age, lower educational and socio-economic status, and alcohol use.

      Conclusions

      Given the high prevalence of LTBI amongst foreign-born residents from regional countries, similar studies should be conducted amongst migrants in Singapore to improve national guidelines on screening and preventive treatment against LTBI.

      Keywords

      Introduction

      Tuberculosis (TB) has killed more than a billion people in the last 200 years and is currently the leading cause of death due to a single infectious agent (
      • World Health Organization
      Global Tuberculosis report 2017.
      ). The emergence of drug-resistant strains and global migration have further complicated the control of this disease (
      • Dheda K.
      • Gumbo T.
      • Gandhi N.R.
      • Murray M.
      • Theron G.
      • Udwadia Z.
      • et al.
      Global control of tuberculosis: from extensively drug-resistant to untreatable tuberculosis.
      ). The World Health Organization (WHO) estimated that there were 10.4 million new cases in 2016, with the WHO South-East Asia Region and WHO Western Pacific Region accounting for 47% and 17%, respectively, of the global burden (
      • World Health Organization
      Global Tuberculosis report 2017.
      ). Latent tuberculosis infection (LTBI) is characterized by a state of continuous immune response to stimulation by Mycobacterium tuberculosis antigens without displaying clinical manifestations of active TB (
      • World Health Organization
      Guidelines on the management of latent tuberculosis infection.
      ). The lifetime risk of TB reactivation for an individual with LTBI is approximately 5–10% (
      • World Health Organization
      Guidelines on the management of latent tuberculosis infection.
      ,
      • US Centers for Disease Control and Prevention (CDC)
      The difference between latent TB infection and TB disease.
      ,
      • Ai J.-W.
      • Ruan Q.-L.
      • Liu Q.-H.
      • Zhang W.-H.
      Updates on the risk factors for latent tuberculosis reactivation and their managements.
      ). The latest global estimates suggest that about 1.7 billion people had LTBI in 2014 (
      • Houben R.M.G.J.
      • Dodd P.J.
      The global burden of latent tuberculosis infection: a re-estimation using mathematical modelling.
      ). Targeted treatment of LTBI, in high risk groups, is the main intervention available to prevent the development of active TB (
      • World Health Organization
      Global Tuberculosis report 2017.
      ,
      • Alsdurf H.
      • Hill P.C.
      • Matteelli A.
      • Getahun H.
      • Menzies D.
      The cascade of care in diagnosis and treatment of latent tuberculosis infection: a systematic review and meta-analysis.
      ,
      • Getahun H.
      • Matteelli A.
      • Abubakar I.
      • Aziz M.A.
      • Baddeley A.
      • Barreira D.
      • et al.
      Management of latent Mycobacterium tuberculosis infection: WHO guidelines for low tuberculosis burden countries.
      ).
      Singapore is an island city state of 719 square kilometres in Southeast Asia. Its total population of 5.64 million comprises a resident population of 3.41 million citizens and 0.53 million Permanent Residents, and 1.7 million foreigners who are granted long-term passes to work, study, or live as dependents in the country (
      • Singapore Department of Statistics
      Latest data—population & land area (mid-year estimates).
      ). Following a decade of decline to a historical low of 35 per 100 000 population in 2007, the TB incidence rate among the residents of Singapore increased in 2008 and has remained at around 40 per 100 000 population (
      • Chee C.B.-E.
      • Wang Y.T.
      TB control in Singapore: where do we go from here?.
      , ) despite the efforts of the Singapore TB Elimination Programme (STEP) (
      • Chee C.B.-E.
      • Wang Y.T.
      TB control in Singapore: where do we go from here?.
      ). Possible factors contributing to this stagnation include (1) ongoing community transmission due to delayed diagnosis of infectious cases, and (2) reactivation of LTBI in a rapidly aging population (who acquired their infection in the remote past when TB rates in Singapore were very high), or among newly inducted citizens or Permanent Residents, the majority of whom are foreign-born and from surrounding high TB incidence countries (
      • Chee C.B.-E.
      • Wang Y.T.
      TB control in Singapore: where do we go from here?.
      ,
      • Wah W.
      • Das S.
      • Earnest A.
      • Lim L.K.Y.
      • Chee C.B.E.
      • Cook A.R.
      • et al.
      Time series analysis of demographic and temporal trends of tuberculosis in Singapore.
      ). Profiling the prevalence of LTBI among long-term residents in Singapore would allow the potential size of the current reservoir of infection to be estimated and an understanding of how this might affect the future incidence of active TB (
      • Kahwati L.C.
      • Feltner C.
      • Halpern M.
      • Woodell C.L.
      • Boland E.
      • Amick H.R.
      • et al.
      Primary care screening and treatment for latent tuberculosis infection in adults: evidence report and systematic review for the US preventive services task force.
      ).
      In view of universal bacille Calmette–Guérin (BCG) vaccination at birth since the 1950s and a BCG re-vaccination programme for school leavers from the 1950s to 2001, it is likely that a tuberculin skin test (TST) survey would overestimate the reservoir of LTBI in the local population (
      • Chee C.B.E.
      • Lim L.K.Y.
      • Barkham T.M.
      • Koh D.R.
      • Lam S.O.
      • Shen L.
      • et al.
      Use of a T cell interferon-gamma release assay to evaluate tuberculosis risk in newly qualified physicians in Singapore healthcare institutions.
      ,
      • Menzies R.
      • Vissandjee B.
      Effect of bacille Calmette-Guérin vaccination on tuberculin reactivity.
      ). This large population-based survey of LTBI in Singapore was performed by utilizing an interferon-gamma release assay (IGRA), the QuantiFERON Gold In-tube assay (QFT-GIT; Qiagen, Hilden, Germany), and represents the first such study. The study aimed to estimate the prevalence of LTBI stratified by key socio-demographic variables, and to compare these estimates with incidence rates of active TB. Groups at risk for LTBI in the resident population of Singapore were also identified to understand underlying drivers of TB epidemiology in Singapore.

      Materials and methods

      Study design

      This was a cross-sectional study conducted between April 2014 and March 2015. The survey was nested within a larger population-based cohort study known as the Singapore Health Study 2 (SH2), which aimed to monitor the health of Singaporeans in preventive health and risk behaviours and chronic non-communicable diseases.

      Study sites

      Across the island city state of Singapore (
      • Singapore Department of Statistics
      Latest data—population & land area (mid-year estimates).
      ), four study sites were set up: SATA CommHealth Clinic at Jurong East, SATA CommHealth Clinic at Woodlands, Cheng San Community Club at Ang Mo Kio, and a data collection centre within Bras Basah Complex in the west, north, north-east, and south-east central regions of Singapore, respectively. All sites were similarly equipped with the necessary amenities for the study.

      Study population

      A random sample of 32 100 household addresses was selected from the National Database on Dwellings in Singapore maintained by the Department of Statistics. The areas considered for selection were those classified under Urban Redevelopment Authority Singapore postal districts 16, 20, 22, and 25, as these districts were near to the various study sites being set up across the country. Under this sampling frame, 15 000 household addresses were selected randomly and notified of the survey by post. Subsequently, house visits were conducted to enumerate all household members who met the following inclusion criteria: (1) must be a Singaporean or Permanent Resident; (2) aged 18–79 years; (3) stayed at least 4 days each week in the household and would be staying for the next 3 months or longer; (4) not pregnant, having a severe mental illness, bedridden, or wheelchair bound. Amongst those households that were successfully enumerated, one member per household was selected to participate in the study using the Kish grid. Assuming a LTBI prevalence of 4.3%, an estimated sample size of 1580 was planned in order to achieve a 95% level of confidence with a precision of 1%.

      Study procedures

      An interviewer-administered electronic questionnaire was used to elicit information on demographic, socio-economic, lifestyle practices relating to disease risk factors, medical history including past diagnosis of TB, and possible exposure to TB. All study team members were briefed extensively on the study methodology and underwent rigorous training to ensure consistency of and compliance with the study procedures.

      Sample processing and laboratory analysis

      Blood samples collected for the QFT-GIT assay were sent to the Department of Laboratory Medicine at Tan Tock Seng Hospital and the National University Hospital Referral Laboratory on the day of collection and were processed, interpreted, and reported as per the manufacturer’s instructions. Samples with indeterminate results were not repeat-tested.

      Data management and analysis

      Responses recorded with the electronic questionnaire were automatically checked for missing values, data type errors, and range sensibility. For quality control, 20% of the surveys were selected randomly and verified against the audio recordings of the interviews. Data anomalies were clarified through direct verification with the respondents whenever necessary. Laboratory test results were provided in electronic format by the laboratory and merged with the rest of the electronic data, which were then subjected to a series of range, logic, and consistency checks. Asymptomatic participants with a positive IGRA result were considered as having LTBI.
      The study sample was weighted to adjust for unequal probability of selection and differential response levels and to account for under-represented groups in the population. For the household enumeration exercise of SH2, sample weights (WEE) comprised weights that were computed based on the dwelling type and region of dwelling. For the study fieldwork of SH2, sample weights (WSF) comprised weights that were computed based on age, sex, and ethnicity. For the LTBI study, sample weights (WIGRA) for IGRA non-response were computed based on age, educational status, and average monthly household income. Post-stratification weights (WPS), to account for under-represented groups in the population, were computed based on ethnicity, age, and sex, with reference to the Singapore resident population as of mid-2014. The overall sample weights were the product of WEE, WSF, WIGRA, and WPS.
      These weights were then applied to the sample to produce weighted estimates of LTBI prevalence, which were also compared against the incidence rates of active TB cases notified for various age, sex, and ethnic strata in 2014 (
      • Ministry of Health Singapore
      Communicable diseases surveillance in Singapore 2014.
      ). To identify independent risk factors, adjusted hazard ratios (HR) were obtained using the multivariable modified Breslow–Cox proportional hazards model. As latent TB is a relatively common condition, odds ratios are not a good approximation of prevalence rate ratios. The Breslow–Cox proportional hazards regression was therefore modified using the method proposed by Lee and Chia, where the adjusted HRs obtained are equivalent to prevalence rate ratios (
      • Lee J.
      • Chia K.S.
      Estimation of prevalence rate ratios for cross sectional data: an example in occupational epidemiology.
      ). Further stratified analyses were also performed on the prevalence of LTBI, history of past diagnoses, and exposure to a household member who had TB, by the participants’ country of birth. The country of birth was determined by a participant’s previous or current citizenship for Singapore citizens and Permanent Residents, respectively. Singaporean citizens who had not previously held citizenship in other countries were considered to be Singapore-born. Permanent Residents and citizens who had previous citizenship elsewhere were considered to be foreign-born.

      Ethical considerations

      The study protocol and procedures were approved by the National University of Singapore Institutional Review Board (NUS IRB reference number 13–512). Written informed consent was obtained from each participant, as well as the parent or legal guardian for participants aged 18–20 years.

      Results

      Characteristics of the study population

      Amongst the 2686 Singapore residents who participated in the SH2 study, 1690 (63%) provided blood for IGRA testing (Table 1). A comparison between IGRA respondents and non-respondents showed significant differences by age, educational status, and monthly household income. After applying the SH2 weights to the IGRA respondents, about 20% each were in the first four age bands up to 59 years of age; 51.0% were female and 76.0% were Chinese. These age, sex, and ethnic distributions were fairly close to those of the Singapore resident population in 2014. However, the census-based estimates of the Singapore resident population had a larger proportion with primary or lesser education than our weighted distribution (30.4% versus 11.5%, respectively), as well as a smaller proportion living in public housing (82.6% versus 91.1%, respectively).
      Table 1Comparison of the socio-demographic and socio-economic profiles between IGRA respondents and non-respondents, and between the weighted sample of IGRA respondents and the Singapore resident population of 2014 (n = 2686).
      CharacteristicsNo. (%) forp-Value
      Chi-square test comparing the distribution of IGRA respondents and non-respondents.
      IGRA respondents, weighted % (95% CI)Singapore resident population 2014, %
      IGRA non-respondents

      n = 996
      IGRA respondents

      n = 1690
      Age group, years
       18–29187 (18.8)245 (14.5)<0.00120.6 (18, 23.3)24.5
       30–39211 (21.2)329 (19.5)19.7 (17.5, 22)18.7
       40–49184 (18.5)422 (25.0)20.7 (18.6, 22.9)19.7
       50–59161 (16.2)355 (21.0)20.1 (17.8, 22.4)19.0
       60–69165 (16.6)268 (15.9)12.9 (10.9, 15)12.4
       70–7988 (8.8)71 (4.2)5.9 (4.2, 7.5)5.8
      Sex
       Female539 (54.1)941 (55.7)0.43151.0 (48.0, 53.9)50.9
       Male457 (45.9)749 (44.3)49.0 (46.1, 52.0)49.1
      Ethnicity
       Chinese644 (64.7)1146 (67.8)0.15276.0 (73.7, 78.3)75.3
       Malay164 (16.5)226 (13.4)12.4 (10.6, 14.2)12.8
       Indian154 (15.5)255 (15.1)8.8 (7.5, 10.1)8.8
       Others34 (3.4)63 (3.7)2.9 (2.0, 3.7)3.1
      Country of birth
       Singapore726 (72.9)1171 (69.3)0.04872.3 (69.7, 74.8)Not available
       Non-Singapore270 (27.1)519 (30.7)27.7 (25.2, 30.3)
      Educational status
       Post-secondary456 (45.8)874 (51.7)<0.00158.7 (55.8, 61.5)51.2
       Secondary339 (34.0)571 (33.8)29.8 (27.2, 32.4)18.4
       Primary or less201 (20.2)245 (14.5)11.5 (9.8, 13.3)30.4
      Dwelling type
       HDB flats (public housing)955 (95.9)1629 (96.4)0.796(88.6, 93.6)82.6
       Condominium19 (1.9)29 (1.7)5.8 (3.6, 8.0)10.8
       Landed property22 (2.2)32 (1.9)3.1 (1.7, 4.5)6.6
      Monthly household income (SGD)
      Excludes 251 respondents who did not provide a valid response.
       <$2000265 (30.1)370 (23.8)0.01017.8 (15.6, 19.9)Not available
       $2000–$3999231 (26.3)457 (29.4)28.8 (26, 31.5)
       $4000–$5999157 (17.8)324 (20.8)22.5 (19.9, 25.1)
       $6000–$9999145 (16.5)263 (16.9)19.8 (17.3, 22.3)
       ≥$10 00082 (9.3)141 (9.1)11.1 (8.9, 13.4)
      CI, confidence interval; IGRA, interferon-gamma release assay.
      a Chi-square test comparing the distribution of IGRA respondents and non-respondents.
      b Excludes 251 respondents who did not provide a valid response.

      Factors associated with having a positive IGRA result

      After excluding eight indeterminate IGRA results, the results of 1682 participants remained for analysis. Of these, 213 (12.7%) had a positive IGRA result. Table 2 shows that the proportion positive by IGRA increased from 2.4% in those aged 18–29 years to 23.2% in those aged 70–79 years (p< 0.001), and 10.6% of females were positive compared with 15.3% of males (p = 0.004). Malays were least likely to have a positive IGRA result (7.5%), followed by Chinese (11.9%), Indians (18.6%), and those of other ethnic groups (20.6%; p = 0.001). Singapore-born respondents were less likely to be positive than foreign-born respondents (10.7% versus 17.2%, respectively; p< 0.001), and there were also significant differences (at p< 0.001) by marital and educational status. In particular, those with the least education were more likely to be positive than those with post-secondary education (22.7% versus 10.3%, respectively). Those with a self-reported past history of a TB diagnosis were significantly and much more likely to have a positive IGRA result (70.4%; p< 0.001). Those reporting a past exposure to a household member with TB were also significantly more likely to be positive than those who did not (21.0% versus 12.2%, respectively; p = 0.021). Ex-smokers and current smokers were more likely to have a positive result, as were those who consumed alcohol more than once a week and those who had been diagnosed with diabetes. However, on multivariable regression, only some of these factors remained positively and significantly associated with a positive IGRA at p< 0.05, namely older age, Indian ethnicity, being foreign-born, having a primary or lesser education, self-reported past history of TB diagnosis, and consuming alcohol more than once a week. Those living in individual properties with privately owned land were less likely to be positive by IGRA (adjusted HR 0.1, 95% confidence interval (CI) 0.0–0.5; p = 0.008).
      Table 2Number of respondents with a positive IGRA result and adjusted hazard ratios for a positive IGRA result by participant characteristics (n = 1682).
      CharacteristicsTotal respondentsNo. (%) positive for LTBIp-Value
      Chi-square test comparing the distribution for those positive and those negative for LTBI.
      Multivariable analysis
      Adjusted HR
      Adjusted hazard ratios obtained using the multivariable modified Breslow–Cox proportional hazards model with robust variance and sampling weights, and including all the variables in the table above.
      (95% CI)
      p-Value
      Age group, years
       18–292466 (2.4)<0.001Ref.
       30–3932738 (11.6)3.4 (1.2, 10.0)0.024
       40–4942251 (12.1)3.5 (1.2, 10.2)0.019
       50–5934957 (16.1)4.3 (1.4, 13.1)0.010
       60–6926545 (17.0)3.9 (1.2, 12.0)0.020
       70–797316 (23.2)7.2 (2.0, 25.5)0.002
      Sex
       Female93699 (10.6)0.004Ref.
       Male746114 (15.3)1.4 (1.0, 2.0)0.049
      Ethnicity
       Chinese1140136 (11.9)0.001Ref.
       Malay22617 (7.5)0.7 (0.4, 1.3)0.290
       Indian25347 (18.6)1.6 (1.1, 2.2)0.015
       Others6313 (20.6)1.2 (0.6, 2.3)0.662
      Country of birth
       Singapore1164124 (10.7)<0.001Ref.
       Non-Singapore51889 (17.2)1.6 (1.1, 2.2)0.007
      Marital status
       Never married/not stated38525 (6.5)<0.001Ref.
       Currently married1104153 (13.9)0.9 (0.5, 1.6)0.755
       Separated/divorced13023 (17.7)1.2 (0.6, 2.6)0.620
       Widowed6312 (19.0)0.8 (0.3, 1.9)0.561
      Educational status
       Post-secondary24255 (22.7)<0.001Ref.
       Secondary56868 (12.0)1.1 (0.7, 1.8)0.554
       Primary or less87290 (10.3)2.1 (1.3, 3.6)0.004
      Dwelling type
       HDB flats (public housing)1621208 (12.8)0.258Ref.
       Condominium294 (13.8)0.7 (0.2, 1.9)0.452
       Landed property321 (3.1)0.1 (0.0, 0.5)0.008
      Monthly household income (SGD)
       <$200036857 (15.5)0.266Ref.
       $2000–$399945557 (12.5)1.5 (0.9, 2.4)0.098
       $4000–$599932341 (12.7)1.3 (0.8, 2.2)0.259
       $6000–$999926324 (9.1)1.1 (0.6, 1.9)0.852
       ≥$10 00014015 (10.7)1.3 (0.7, 2.7)0.422
       Not stated13319 (14.3)1.8 (1.0, 3.1)0.053
      Past history of TB diagnosis
       No1655194 (11.7)<0.001Ref.
       Yes2719 (70.4)5.8 (3.7, 9.0)<0.001
      Exposed to TB in household member
       No1601196 (12.2)0.021Ref.
       Yes8117 (21.0)1.1 (0.6, 2.1)0.699
      Smoking status
       Never a smoker1298148 (11.4)0.015Ref.
       Ex-smoker14426 (18.1)1.2 (0.7, 2.0)0.533
       Current occasional smoker424 (9.5)1.0 (0.4, 2.8)0.990
       Current daily smoker19835 (17.7)1.3 (0.8, 2.0)0.344
      Alcohol consumption
       None855111 (13.0)<0.001Ref.
       Less than once per month48751 (10.5)1.0 (0.7, 1.5)0.864
       Several days per month17815 (8.4)0.9 (0.5, 1.5)0.647
       More than once per week16236 (22.2)1.8 (1.2, 2.8)0.009
      Diagnosed with diabetes
       No1546180 (11.6)<0.001Ref.
       Yes13633 (24.3)1.4 (0.9, 2.2)0.128
      CI, confidence interval; HR, hazard ratio; IGRA, interferon-gamma release assay; LTBI, latent tuberculosis infection.
      a Chi-square test comparing the distribution for those positive and those negative for LTBI.
      b Adjusted hazard ratios obtained using the multivariable modified Breslow–Cox proportional hazards model with robust variance and sampling weights, and including all the variables in the table above.

      Variation by country of birth

      Amongst those who were foreign-born, the proportion positive by IGRA varied greatly by country of birth (Table 3). The highest prevalence of 30.8% was observed in those from India, followed by participants from Southeast Asian countries (27.0%) and those from China (17.1%), with the prevalence amongst Singapore-born participants (10.7%) being significantly lower (p< 0.001 versus India and also other Southeast Asian countries, and p = 0.043 for China). Participants from Malaysia had a prevalence that was slightly but not significantly lower (7.3%; p = 0.140) and the small number from other countries had a prevalence that was slightly but not significantly higher (11.5%; p = 0.885).
      Table 3Past history of TB diagnosis, contact with TB, and proportion with a positive IGRA result by country of birth (n = 1682).
      Country of birthTotal respondents, n = 1682
      Excludes eight participants with indeterminate IGRA results.
      No. (%) of respondents with:No. (%) of positive IGRA with past TB or exposure history
      Denominator for the percentage here is the number with a positive IGRA result.
      LTBIPast history of TB diagnosisExposed to TB in household memberEither history of TB or exposure to TB
      All respondents1682213 (12.7)27 (1.6)81 (4.8)100 (5.9)33 (15.5)
      Singapore1164124 (10.7)16 (1.4)64 (5.5)74 (6.4)20 (16.1)
      Non-Singapore51889 (17.2)11 (2.1)17 (3.3)26 (5.0)13 (14.6)
       Malaysia20615 (7.3)1 (0.5)5 (2.4)6 (2.9)1 (6.7)
       Other Southeast Asia
      Includes Indonesia, Thailand, Philippines, Myanmar, Vietnam, Cambodia, Laos, and Brunei.
      7420 (27.0)3 (4.1)3 (4.1)5 (6.8)3 (15.0)
       China10518 (17.1)1 (1.0)6 (5.7)7 (6.7)2 (11.1)
       India10733 (30.8)5 (4.7)3 (2.8)7 (6.5)6 (18.2)
       Other countries263 (11.5)1 (3.8)0 (0.0)1 (3.8)1 (33.3)
      Key high burden countries
      Other Southeast Asia, China, or India.
      28671 (24.8)9 (3.1)12 (4.2)19 (6.6)11 (15.5)
      IGRA, interferon-gamma release assay; LTBI, latent tuberculosis infection.
      a Excludes eight participants with indeterminate IGRA results.
      b Denominator for the percentage here is the number with a positive IGRA result.
      c Includes Indonesia, Thailand, Philippines, Myanmar, Vietnam, Cambodia, Laos, and Brunei.
      d Other Southeast Asia, China, or India.
      Self-reported past history of a TB diagnosis was uncommon in those from Singapore (only 1.4%), and lower than those from other Southeast Asian countries (4.1%; p = 0.100) and India (4.7%; p = 0.026). History of exposure to TB in a household member was reported by 5.5% of Singapore-born participants, which was not significantly different from that reported by foreign-born participants. In all, while 5.9% of respondents reported having either a past TB diagnosis or an exposure to TB, only 33 of these 100 respondents had a positive IGRA result. Moreover, these 33 individuals with past TB or an exposure history represented only 15.5% of all the 213 respondents with a positive IGRA result.
      Since China, India, and most of the other Southeast Asian countries are classified by the WHO as high burden countries (
      • World Health Organization
      Global Tuberculosis report 2017.
      ) and contribute substantially to the population of naturalized citizens and Permanent Residents in Singapore, respondents from these countries were grouped together when performing additional age-stratified analyses. As expected, there was an increasing trend in the proportion positive by IGRA with age, both amongst Singapore-born participants and those born in key high burden countries (Figure 1). Amongst those Singapore-born, the prevalence increased from 2.0% (95% CI 0.5–5.1%) in those aged 18–29 years to 23.3% (95% CI 13.4–36.0%) in those aged 70–79 years. For those from key high burden countries, the prevalence in the youngest age group was similar to that in the Singapore-born, at 3.3% (95% CI 0.1–17.2%). However, there was a marked difference amongst respondents between the ages of 30 and 49 years. For those from key high burden countries, LTBI prevalence was 20.8% (95% CI 14.1–29.0%) in those aged 30–39 years and 30.1% (95% CI 21.0–40.5%) in those aged 40–49 years; this was 3.2 and 4.0 times the respective prevalence in Singapore-born participants (6.6%, 95% CI 3.2–11.8%; and 7.5%, 95% CI 4.5–11.6%).
      Figure 1
      Figure 1Comparison of latent tuberculosis infection (LTBI) prevalence by age group in participants born in ‘Singapore’ (green diamonds) against those from ‘key high burden countries’ (orange triangles) and ‘other countries’ (blue circles). Key high burden countries include China, India, and other Southeast Asian countries besides Malaysia (which is included under ‘other countries’). (Note: Error bars denote 95% confidence intervals.)

      Comparison of LTBI prevalence and incidence rates for active TB

      Lastly, the sampling weights were used to estimate the prevalence in various socio-demographic strata for which TB notification data were available (Figure 2). The overall weighted LTBI prevalence was 10.7% (95% CI 9.0–12.4%) when including all respondents, but 9.2% (95% CI 7.2–11.1%) when restricted to Singapore-born respondents. Amongst all respondents, the weighted prevalence in females (8.8%, 95% CI 6.7–11.0%) was lower than that in males (12.7%, 95% CI 13.8–19.1%). The same trend was also observed when only Singapore-born respondents were included in the analysis (6.4%, 95% CI 4.0–8.8% versus 11.8%, 95% CI 8.7–14.9%). In contrast to the results in Table 2 and the high weighted prevalence of LTBI in Indians amongst all respondents seen in Figure 2A (17.2%, 95% CI 11.7–22.7%), Singapore-born Indians had an LTBI prevalence (7.0%, 95% CI 2.3–11.7%) similar to Malays (6.6%, 95% CI 2.3–10.9%) and lower than in Chinese (9.9%, 95% CI 7.5–12.3%). Notably, although Malays had the lowest prevalence of LTBI, they had the highest incidence rates of active TB (about 1.6 times that for Chinese).
      Figure 2
      Figure 2Weighted latent tuberculosis infection (LTBI) in comparison to notified cases of active TB per 100 000 population (blue bars) in citizens and Singapore Permanent Residents by (A) sex and ethnicity, and (B) age group. Orange circles and green diamonds give the prevalence estimated with the sample weights for all respondents and just the Singapore-born, respectively. (Note: Error bars denote 95% confidence intervals. The group aged <30 years for LTBI prevalence includes participants aged 18–29 years, while the TB notification data were based on those aged 20–29 years.)
      Estimates of LTBI prevalence were markedly higher when including all respondents versus only Singapore-born aged 30–39 years (9.8% versus 6.3%, respectively) and those aged 40–49 years (11.5% versus 7.1%, respectively). In those aged 70–79 years, LTBI prevalence was higher when including only the Singapore-born (29.4%, 95% CI 14.1–44.7% versus 26.0%, 95% CI 12.5–39.4% when including all respondents). Both LTBI prevalence and age-stratified incidence rates of active TB increased with age, with the two showing reasonable correlation across the age groups.

      Discussion

      This cross-sectional population survey found an overall IGRA (QFT-GIT) positivity rate of 12.7% in Singapore residents, from which a weighted LTBI prevalence of 10.7% was derived. There was a wide variation in IGRA positivity according to the participants’ country of birth, reflecting the TB rates of these countries. This ranged from 7.3% and 10.7% in those born in Malaysia and Singapore, respectively, to 27% and 30% among residents born in Southeast Asian countries and India, respectively. Not unexpectedly, the weighted LTBI prevalence increased with age, with a prevalence of 29.4% among Singapore-born aged 70–79 years. Higher LTBI prevalence was also not unexpectedly associated with lower educational and socio-economic status and alcohol use.
      The strength of this study is the large population surveyed with accredited laboratory testing. The interpretation of the study findings should take into account the QFT-GIT sensitivity of 83% in the local population using culture-positive pulmonary TB as a surrogate (
      • Chee C.B.E.
      • Gan S.H.
      • Khinmar K.W.
      • Barkham T.M.
      • Koh C.K.
      • Liang S.
      • et al.
      Comparison of sensitivities of two commercial gamma interferon release assays for pulmonary tuberculosis.
      ) and its possible waning in persons who have been treated (
      • Chee C.B.E.
      • KhinMar K.W.
      • Gan S.H.
      • Barkham T.M.
      • Koh C.K.
      • Shen L.
      • et al.
      Tuberculosis treatment effect on T-cell interferon-gamma responses to Mycobacterium tuberculosis-specific antigens.
      ) or after years of infection (
      • Mori T.
      • Harada N.
      • Higuchi K.
      • Sekiya Y.
      • Uchimura K.
      • Shimao T.
      Waning of the specific interferon-gamma response after years of tuberculosis infection.
      ). Other study limitations are the low response rate to blood taking for the IGRA (only 63% of the study participants provided blood for QFT-GIT) and the significant differences by age, educational and socioeconomic status between the IGRA respondents and non-respondents. Sampling and post-stratification weights were used to account for differential sampling rates in major population sub-groups and for differential non-response rates. This standard approach to handling survey data should reduce bias and improve the stability of estimates. However, selection bias may not be adequately removed even after weighting, especially if the variables available for weighting insufficiently account for the probability of non-response. Further, the derivation of weights in complicated designs such as in this study may not sufficiently correct for population representativeness. Interpretations of the study findings need to take into account these limitations. Finally, although the household addresses were selected only from districts near the various study sites, it was ensured that the locations of the study sites were extensive and covered the west, north, north-east, and south-east central regions of Singapore.
      It was surprising that the Malays who have the highest TB incidence rate among the three main ethnic groups in Singapore, had the lowest LTBI prevalence among these groups. A study found TB patients of Malay ethnicity in Singapore to have significantly more infectious (i.e., sputum smear-positive and cavitary) disease, and to be clustered at the same residential address, implying increased transmission within their community (
      • Lim L.K.-Y.
      • Enarson D.A.
      • Reid A.J.
      • Satyanarayana S.
      • Cutter J.
      • Kyi Win K.M.
      • et al.
      Notified tuberculosis among Singapore residents by ethnicity, 2002-2011.
      ). Malay TB patients were also more likely to be diabetic. A possible reason for the unexpectedly low LTBI prevalence in this group may be the lack of representativeness of the sample population. Another possibility may be the difference in the IGRA performance between ethnic groups. A study comparing the T-SPOT.TB and QFT-GIT in patients with culture-positive pulmonary TB at the Singapore TB Control Unit found IGRAs to be less sensitive in Malays and Indians compared to the Chinese population (
      • Chee C.B.E.
      • Gan S.H.
      • Khinmar K.W.
      • Barkham T.M.
      • Koh C.K.
      • Liang S.
      • et al.
      Comparison of sensitivities of two commercial gamma interferon release assays for pulmonary tuberculosis.
      ). It may also be hypothesized that this ethnic group may be genetically predisposed to a higher risk of progression to active disease once latently infected. This would be worthy of investigation in future studies.
      It appears that reports of population-wide surveys utilizing IGRAs have thus far been few. The United States (US) National Health and Nutrition Examination Survey (NHANES) 2011–2012 utilized the TST and IGRA (QFT-GIT) to estimate the prevalence of TB infection (
      • Miramontes R.
      • Hill A.N.
      • Yelk Woodruff R.S.
      • Lambert L.A.
      • Navin T.R.
      • Castro K.G.
      • et al.
      Tuberculosis infection in the United States: prevalence estimates from the National Health and Nutrition Examination Survey, 2011-2012.
      ). Using the TST, they found no difference in the estimated prevalence of TST positivity rate from 1999–2000 (4.3%) to 2011–2012 (4.7%) despite a continuing decline in TB disease in the USA over the same period. The IGRA-positive rate in 2011–2012 was 5.0% and double TST and IGRA positivity was 2.1%. The point estimate of IGRA positivity prevalence in foreign-born persons was lower than that for the TST (15.9% versus 20.5%), possibly due to false TST positivity as a result of cross-reactivity with BCG. A population-based, multicentre study in rural China that used both the TST and QFT-GIT also showed higher TST positivity rates (15–42%) compared to QFT-GIT (13–20%), suggesting that the prevalence of LTBI in China may be overestimated by the TST (
      • Gao L.
      • Lu W.
      • Bai L.
      • Wang X.
      • Xu J.
      • Catanzaro A.
      • et al.
      LATENTTB-NSTM study team, Latent tuberculosis infection in rural China: baseline results of a population-based, multicentre, prospective cohort study.
      ). In contrast, a population-based survey in Saudi Arabia (where BCG is routinely given at birth) showed similar LTBI prevalence using the TST (9.3%) and QFT-GIT (9.1%), with an annual risk of TB infection (ARTI) of 0.36% using the TST and 0.35% using QFT-GIT (
      • Balkhy H.H.
      • El Beltagy K.
      • El-Saed A.
      • Aljasir B.
      • Althaqafi A.
      • Alothman A.F.
      • et al.
      Prevalence of latent Mycobacterium tuberculosis infection (LTBI) in Saudi Arabia; population based survey.
      ). A study utilizing TST and QFT-GIT to assess ARTI among school children in Spain found a much lower ARTI calculated using the QFT-GIT (0.12%) than that using the TST (0.60%) (
      • Díez N.
      • Giner E.
      • Latorre I.
      • Lacoma A.
      • Roig F.-J.
      • Mialdea I.
      • et al.
      Use of interferon-gamma release assays to calculate the annual risk of tuberculosis infection.
      ).
      Information on the background prevalence of LTBI in Singapore residents gleaned from this study provides evidence-based guidance to the STEP, which has, since 1998, performed contact investigation to identify recently infected contacts who are at high risk for progression to active disease and are candidates for preventive therapy (
      • Chee C.B.E.
      • Teleman M.D.
      • Boudville I.C.
      • Do S.E.
      • Wang Y.T.
      Treatment of latent TB infection for close contacts as a complementary TB control strategy in Singapore.
      ). Contact screening is performed according to concentric circles of exposure to the infectious index case starting with the innermost circle, and the decision to expand screening based on the attack rate of each circle (
      • Veen J.
      Microepidemics of tuberculosis: the stone-in-the-pond principle.
      ). Generally, no further expansion of screening would be required when the attack rate approaches the background LTBI rate of the community. Knowledge of the age-stratified LTBI prevalence in the community is thus useful to guide contact investigations, particularly in schools and nursing homes.
      Since 2005, there has been a marked increase in the number of foreign-born residents and non-residents from high TB incidence countries in Singapore, with a concomitant increase in the number of TB cases among this population, such that foreign-born TB cases constitute more than 40% of the total TB burden in Singapore (). The high LTBI prevalence among residents from surrounding Southeast Asian countries and India gives a forecast of the future TB situation in Singapore. Some may argue for the screening of immigrants from high TB burden countries for LTBI treatment (
      • Getahun H.
      • Matteelli A.
      • Abubakar I.
      • Aziz M.A.
      • Baddeley A.
      • Barreira D.
      • et al.
      Management of latent Mycobacterium tuberculosis infection: WHO guidelines for low tuberculosis burden countries.
      ). While this may have its merits in low TB incidence countries, the feasibility and cost-effectiveness of this intervention in Singapore should be more carefully explored. Until less costly screening tools with higher positive predictive values than the current IGRAs and shorter preventive therapy regimens with negligible adverse effects become available, the country’s resources may be better utilized for higher priority TB control activities, namely early detection and treatment of active TB cases, infection control, and contact screening.

      Conclusion

      This first LTBI prevalence study in Singapore sheds light on the reservoir of TB infection and the potential size of the problem of TB in the country. It provides useful information to the national TB programme in its implementation of contact screening. Sequential surveys to determine the trend in prevalence of TB infection in the community should be performed to aid the ongoing battle against this ancient disease of man.

      Acknowledgements

      We would like to thank the Singaporean residents who took time to participate in this study.

      Funding

      The study was funded by the Ministry of Health, Singapore, under the CD-PHRG (grant number MOHCS14MAR001). The funder had no role in the study design, data collection and analysis, or preparation of the manuscript. The corresponding author has full access to all data in the study and final responsibility for the decision to submit for publication.

      Conflict of interest

      All authors declare no competing interests.

      Author contributions

      WYL, TB, MC, YTW and CC were integral to the study conception and development of the methodology. WYL, YTW, CC and LT were involved in the questionnaire design and acquisition of the data. PY, KT, WYL, MC and CC participated in the analysis and interpretation of the data. PY, KT, TB, MC, YTW and CC drafted and provided critical revisions to the manuscript.

      References

        • Ai J.-W.
        • Ruan Q.-L.
        • Liu Q.-H.
        • Zhang W.-H.
        Updates on the risk factors for latent tuberculosis reactivation and their managements.
        Emerg Microbes Infect. 2016; 5: e10https://doi.org/10.1038/emi.2016.10
        • Alsdurf H.
        • Hill P.C.
        • Matteelli A.
        • Getahun H.
        • Menzies D.
        The cascade of care in diagnosis and treatment of latent tuberculosis infection: a systematic review and meta-analysis.
        Lancet Infect Dis. 2016; 16: 1269-1278https://doi.org/10.1016/S1473-3099(16)30216-X
        • Balkhy H.H.
        • El Beltagy K.
        • El-Saed A.
        • Aljasir B.
        • Althaqafi A.
        • Alothman A.F.
        • et al.
        Prevalence of latent Mycobacterium tuberculosis infection (LTBI) in Saudi Arabia; population based survey.
        Int J Infect Dis. 2017; 60: 11-16https://doi.org/10.1016/j.ijid.2017.03.024
        • Chee C.B.-E.
        • Wang Y.T.
        TB control in Singapore: where do we go from here?.
        Singapore Med J. 2012; 53: 236-238
        • Chee C.B.E.
        • Teleman M.D.
        • Boudville I.C.
        • Do S.E.
        • Wang Y.T.
        Treatment of latent TB infection for close contacts as a complementary TB control strategy in Singapore.
        Int J Tuberc Lung Dis. 2004; 8: 226-231
        • Chee C.B.E.
        • Gan S.H.
        • Khinmar K.W.
        • Barkham T.M.
        • Koh C.K.
        • Liang S.
        • et al.
        Comparison of sensitivities of two commercial gamma interferon release assays for pulmonary tuberculosis.
        J Clin Microbiol. 2008; 46: 1935-1940https://doi.org/10.1128/JCM.02403-07
        • Chee C.B.E.
        • Lim L.K.Y.
        • Barkham T.M.
        • Koh D.R.
        • Lam S.O.
        • Shen L.
        • et al.
        Use of a T cell interferon-gamma release assay to evaluate tuberculosis risk in newly qualified physicians in Singapore healthcare institutions.
        Infect Control Hosp Epidemiol. 2009; 30: 870-875https://doi.org/10.1086/599284
        • Chee C.B.E.
        • KhinMar K.W.
        • Gan S.H.
        • Barkham T.M.
        • Koh C.K.
        • Shen L.
        • et al.
        Tuberculosis treatment effect on T-cell interferon-gamma responses to Mycobacterium tuberculosis-specific antigens.
        Eur Respir J. 2010; 36: 355-361https://doi.org/10.1183/09031936.00151309
        • Díez N.
        • Giner E.
        • Latorre I.
        • Lacoma A.
        • Roig F.-J.
        • Mialdea I.
        • et al.
        Use of interferon-gamma release assays to calculate the annual risk of tuberculosis infection.
        Pediatr Infect Dis J. 2015; 34: 219-221https://doi.org/10.1097/INF.0000000000000514
        • Dheda K.
        • Gumbo T.
        • Gandhi N.R.
        • Murray M.
        • Theron G.
        • Udwadia Z.
        • et al.
        Global control of tuberculosis: from extensively drug-resistant to untreatable tuberculosis.
        Lancet Respir Med. 2014; 2: 321-338https://doi.org/10.1016/S2213-2600(14)70031-1
        • Gao L.
        • Lu W.
        • Bai L.
        • Wang X.
        • Xu J.
        • Catanzaro A.
        • et al.
        LATENTTB-NSTM study team, Latent tuberculosis infection in rural China: baseline results of a population-based, multicentre, prospective cohort study.
        Lancet Infect Dis. 2015; 15: 310-319https://doi.org/10.1016/S1473-3099(14)71085-0
        • Getahun H.
        • Matteelli A.
        • Abubakar I.
        • Aziz M.A.
        • Baddeley A.
        • Barreira D.
        • et al.
        Management of latent Mycobacterium tuberculosis infection: WHO guidelines for low tuberculosis burden countries.
        Eur Respir J. 2015; 46: 1563-1576https://doi.org/10.1183/13993003.01245-2015
        • Houben R.M.G.J.
        • Dodd P.J.
        The global burden of latent tuberculosis infection: a re-estimation using mathematical modelling.
        PLoS Med. 2016; 13e1002152https://doi.org/10.1371/journal.pmed.1002152
        • Kahwati L.C.
        • Feltner C.
        • Halpern M.
        • Woodell C.L.
        • Boland E.
        • Amick H.R.
        • et al.
        Primary care screening and treatment for latent tuberculosis infection in adults: evidence report and systematic review for the US preventive services task force.
        JAMA. 2016; 316: 970-983https://doi.org/10.1001/jama.2016.10357
        • Lee J.
        • Chia K.S.
        Estimation of prevalence rate ratios for cross sectional data: an example in occupational epidemiology.
        Br J Ind Med. 1993; 50: 861-862
        • Lim L.K.-Y.
        • Enarson D.A.
        • Reid A.J.
        • Satyanarayana S.
        • Cutter J.
        • Kyi Win K.M.
        • et al.
        Notified tuberculosis among Singapore residents by ethnicity, 2002-2011.
        Public Health Action. 2013; 3: 311-316https://doi.org/10.5588/pha.13.0055
        • Menzies R.
        • Vissandjee B.
        Effect of bacille Calmette-Guérin vaccination on tuberculin reactivity.
        Am Rev Respir Dis. 1992; 145: 621-625https://doi.org/10.1164/ajrccm/145.3.621
        • Ministry of Health Singapore
        Communicable diseases surveillance in Singapore 2014.
        2015
        • Ministry of Health Singapore
        Communicable diseases surveillance in Singapore 2017.
        2017
        • Miramontes R.
        • Hill A.N.
        • Yelk Woodruff R.S.
        • Lambert L.A.
        • Navin T.R.
        • Castro K.G.
        • et al.
        Tuberculosis infection in the United States: prevalence estimates from the National Health and Nutrition Examination Survey, 2011-2012.
        PLoS One. 2015; 10e0140881https://doi.org/10.1371/journal.pone.0140881
        • Mori T.
        • Harada N.
        • Higuchi K.
        • Sekiya Y.
        • Uchimura K.
        • Shimao T.
        Waning of the specific interferon-gamma response after years of tuberculosis infection.
        Int J Tuberc Lung Dis. 2007; 11: 1021-1025
        • Singapore Department of Statistics
        Latest data—population & land area (mid-year estimates).
        2016 (https://www.singstat.gov.sg/statistics/latest-data#16. [Accessed 3 May 2018])
        • US Centers for Disease Control and Prevention (CDC)
        The difference between latent TB infection and TB disease.
        2014 (https://www.cdc.gov/tb/publications/factsheets/general/ltbiandactivetb.htm. [Accessed 3 May 2018])
        • Veen J.
        Microepidemics of tuberculosis: the stone-in-the-pond principle.
        Tuber Lung Dis. 1992; 73: 73-76https://doi.org/10.1016/0962-8479(92)90058-R
        • Wah W.
        • Das S.
        • Earnest A.
        • Lim L.K.Y.
        • Chee C.B.E.
        • Cook A.R.
        • et al.
        Time series analysis of demographic and temporal trends of tuberculosis in Singapore.
        BMC Public Health. 2014; 14: 1121https://doi.org/10.1186/1471-2458-14-1121
        • World Health Organization
        Guidelines on the management of latent tuberculosis infection.
        World Health Organization, Geneva, Switzerland2015 (http://www.who.int/tb/publications/ltbi_document_page/en/. [Accessed 3 May 2018])
        • World Health Organization
        Global Tuberculosis report 2017.
        World Health Organization, Geneva, Switzerland2017