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Investigating the risk factors for contraction and diagnosis of human tuberculosis in Indonesia using data from the fifth wave of RAND’s Indonesian Family Life Survey (IFLS-5)

Published online by Cambridge University Press:  17 August 2020

Nathan Adam Open the ORCID record for Nathan Adam [Opens in a new window] ,
Saseendran Pallikadavath Open the ORCID record for Saseendran Pallikadavath [Opens in a new window] ,
Marianna Cerasuolo Open the ORCID record for Marianna Cerasuolo [Opens in a new window]  and
Mark Amos Open the ORCID record for Mark Amos [Opens in a new window]
Nathan Adam*
Affiliation:
Portsmouth-Brawijaya Centre for Global Health, Population, and Policy, University of Portsmouth, UK
Saseendran Pallikadavath
Affiliation:
Portsmouth-Brawijaya Centre for Global Health, Population, and Policy, University of Portsmouth, UK
Marianna Cerasuolo
Affiliation:
School of Mathematics and Physics, University of Portsmouth, UK
Mark Amos
Affiliation:
Portsmouth-Brawijaya Centre for Global Health, Population, and Policy, University of Portsmouth, UK
*
*Corresponding author. Email: [email protected]
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Abstract

Tuberculosis (TB) is a globally widespread disease, with approximately a quarter of the world’s population currently infected (WHO, 2018). Some risk factors, such as HIV status, nutrition and body mass index, have already been thoroughly investigated. However, little attention has been given to behavioural and/or psychological risk factors such as stress and education level. This study investigated the risk factors for TB diagnosis by statistical analyses of publicly available data from the most recent wave of the Indonesian Family Life survey (IFLS-5) conducted in 2015. Out of 34,249 respondents there were 328 who reported having TB. For comparison and completeness, variables were divided into levels: individual-, household- and community-level variables. The most prominent and interesting variables found to influence TB diagnosis status (on each level) were investigated, and a logistic regression was subsequently developed to understand the extent to which each risk factor acts as a predictor for being diagnosed with TB. Age, health benefit or insurance, stress at work and living in a rural area all showed significant association with TB diagnosis status. This study’s findings suggest that suitable control measures, such as schemes for improving mental health/stress reduction and improved access to health care in rural areas should be implemented in Indonesia to address each of the key factors identified.

Keywords

Risk factorsLogistic regressionTuberculosis
Type
Research Article
Information
Journal of Biosocial Science , Volume 53 , Issue 4 , July 2021 , pp. 577 - 589
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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References

Amo-Adjei, J (2016) Individual, household and community level factors associated with keeping tuberculosis status secret in Ghana. BMC Public Health 16(1), 1196.CrossRefGoogle ScholarPubMed
Baker, DP, Leon, J, Smith-Greenaway, EG, Collins, J and Movit, M (2011) The education effect on population health: a reassessment. Population and Development Review 37(2), 307–332.CrossRefGoogle ScholarPubMed
Barnes, PF, Le, HQ and Davidson, PT (1993) Tuberculosis in patients with HIV infection. Medical Clinics of North America 77(6), 1369–1390.CrossRefGoogle ScholarPubMed
Bates, MN, Khalakdina, A, Pai, M, Chang, L, Lessa, F and Smith, KR (2007) Risk of tuberculosis from exposure to tobacco smoke: a systematic review and meta-analysis. Archives of Internal Medicine 167(4), 335–342.CrossRefGoogle ScholarPubMed
Bhunu, C, Mushayabasa, S and Smith, R (2012) Assessing the effects of poverty in tuberculosis transmission dynamics. Applied Mathematical Modelling 36(9), 4173–4185.Google Scholar
Blower, SM, Mclean, AR, Porco, TC, Small, PM, Hopewell, PC, Sanchez, MA and Moss, AR (1995) The intrinsic transmission dynamics of tuberculosis epidemics. Nature Medicine 1(8), 815–821.CrossRefGoogle ScholarPubMed
Bock, P and Cox, H (2017) Acute care – an important component of the continuum of care for HIV and tuberculosis in developing countries. Anaesthesia 72(2), 147–150.CrossRefGoogle ScholarPubMed
Cohen, S, Murphy, ML and Prather, AA (2019) Ten surprising facts about stressful life events and disease risk. Annual Review of Psychology 70, 577–597.CrossRefGoogle ScholarPubMed
Collins, D, Hafidz, F and Mustikawati, D (2017) The economic burden of tuberculosis in Indonesia. International Journal of Tuberculosis and Lung Disease 21(9), 1041–1048.CrossRefGoogle ScholarPubMed
Daniel, TM (2006) The history of tuberculosis. Respiratory Medicine 100(11), 1862–1870.CrossRefGoogle ScholarPubMed
Davis, AL (2000) A historical perspective on tuberculosis and its control. In Reichman, LB and Earl, SH (eds) Tuberculosis: A Comprehensive International Approach. CRC Press, Boca Raton, FL, pp. 3–54.Google Scholar
de Oliveira, HB and Moreira Filho, DDC (2000) Tuberculosis recurrence and its risk factors. Pan American Journal of Public Health 7(4), 232–241.Google ScholarPubMed
Dhabhar, FS and McEwen, BS (1999) Enhancing versus suppressive effects of stress hormones on skin immune function. Proceedings of the National Academy of Sciences of the USA 96(3), 1059–1064.CrossRefGoogle ScholarPubMed
Duarte, R, Lönnroth, K, Carvalho, C, Lima, F, Carvalho, A, Muñoz-Torrico, M and Centis, R (2018) Tuberculosis, social determinants and co-morbidities (including HIV). Pulmonology 24(2), 115–119.CrossRefGoogle Scholar
Dye, C, Scheele, S, Dolin, P, Pathania, V and Raviglione, MC (1999) Global burden of tuberculosis: estimated incidence, prevalence, and mortality by country. JAMA 282(7), 677–686.CrossRefGoogle ScholarPubMed
Fogel, N (2015) Tuberculosis: a disease without boundaries. Tuberculosis 95(5), 527–531.CrossRefGoogle ScholarPubMed
Fuady, A, Houweling, TA, Mansyur, M and Richardus, JH (2018) Catastrophic total costs in tuberculosis-affected households and their determinants since Indonesia’s implementation of universal health coverage. Infectious Diseases of Poverty 7(1), 3.CrossRefGoogle ScholarPubMed
Hosmer, DW Jr, Lemeshow, S and Sturdivant, RX (2013) Applied Logistic Regression, Vol. 398. John Wiley & Sons.CrossRefGoogle Scholar
Keflie, TS, Samuel, A, Woldegiorgis, AZ, Mihret, A, Abebe, M and Biesalski, HK (2018) Vitamin A and zinc deficiencies among tuberculosis patients in Ethiopia. Journal of Clinical Tuberculosis and other Mycobacterial Diseases 12, 27–33.CrossRefGoogle ScholarPubMed
Keller, PM (2018) Urban transmission of tuberculosis in China. The Lancet Infectious Diseases 18(7), 706–707.CrossRefGoogle ScholarPubMed
Marçôaa, R (2018) Tuberculosis and gender – factors influencing the risk of tuberculosis among men and women by age group. Pulmonology 24(3), 199–202.CrossRefGoogle Scholar
Mason, PH, Roy, A and Singh, P (2017) Reciprocity-building and the importance of interdisciplinary collaboration in tuberculosis research. Journal of Biosocial Science 49(4), 559–562.CrossRefGoogle ScholarPubMed
Mason, PH, Roy, A, Spillane, J and Singh, P (2016) Social, historical and cultural dimensions of tuberculosis. Journal of Biosocial Science 48(2), 206–232.CrossRefGoogle ScholarPubMed
Morey, JN, Boggero, IA, Scott, AB and Segerstrom, SC (2015) Current directions in stress and human immune function. Current Opinion in Psychology 5, 13–17.CrossRefGoogle ScholarPubMed
O’Donnell, O (2007) Access to health care in developing countries: breaking down demand side barriers. Cadernos de Saude Publica 23(12), 2820–2834.CrossRefGoogle ScholarPubMed
Organisation for Economic Co-operation and Development (2018) Employment: Labour Force Participation, by Sex and Age Group. URL: https://stats.oecd.org/index.aspx?queryid=54741 (accessed 21st May 2020).Google Scholar
Pawelec, G (2018) Age and immunity: what is ‘immunosenescence’? Experimental Gerontology 105, 4–9.CrossRefGoogle Scholar
RAND (2018) RAND IFLS-5 Survey Description. URL: https://www.rand.org/well-being/social-and-behavioral-policy/data/FLS/IFLS/ifls5.html (accessed 21st May 2020).Google Scholar
Ranganathan, P, Pramesh, CS and Aggarwal, R (2017) Common pitfalls in statistical analysis: logistic regression. Perspectives in Clinical Research 8(3), 148.Google ScholarPubMed
Rim, KT and Lim, CH (2014) Biologically hazardous agents at work and efforts to protect workers’ health: a review of recent reports. Safety and Health at Work 5(2), 43–52.CrossRefGoogle ScholarPubMed
Sahiratmadja, E and Nagelkerke, N (2016) Smoking habit as a risk factor in tuberculosis: a case-control study. Universa Medicina 30(3), 189–196 Google Scholar
Shajahan, R, Navaratnam, P, Kasinathan, G, Kadirvelu, A and Pillai, N (2016) Predictors of re-emerging tuberculosis: a review. Open Access Library Journal 3(3), 1–18.Google Scholar
Simandan, D (2010) On how much one can take: relocating exploitation and exclusion within the broader framework of allostatic load theory. Health & Place 16(6), 1291–1293.CrossRefGoogle ScholarPubMed
Simandan, D (2017a) Considering neoliberalism, contempt and allostatic load in the social dynamics of tuberculosis. Journal of Biosocial Science 49(4), 557–558.CrossRefGoogle ScholarPubMed
Simandan, D (2017b) Wisdom and the path-dependent politics of biomedical research. Journal of Biosocial Science 49(4), 563–565.CrossRefGoogle ScholarPubMed
Nhamoyebonde, S and Leslie, A (2014) Biological differences between the sexes and susceptibility to tuberculosis. Journal of Infectious Diseases 209 (Supplement 3), S100–S106.CrossRefGoogle ScholarPubMed
WHO (2007) A WHO/The Union Monograph on TB and Tobacco Control: Joining Efforts to Control Two Related Global Epidemics. World Health Organization, Geneva. URL: https://apps.who.int/iris/handle/10665/43812 (accessed 21st May 2020).Google Scholar
WHO (2018) Global Tuberculosis Report 2018. World Health Organization, Geneva URL: https://www.who.int/tb/publications/global_report/en/ (accessed 21st May 2020).Google Scholar
Zvonareva, O, van Bergen, W, Kabanets, N, Alliluyev, A and Filinyuk, O (2019) Experiencing syndemic: disentangling the biosocial complexity of tuberculosis through qualitative research. Journal of Biosocial Science 51(3), 403–417.CrossRefGoogle ScholarPubMed